US9927976B2 - Storing data in a directory-less dispersed storage network - Google Patents

Abstract

A method begins by a dispersed storage (DS) processing module of a dispersed storage network (DSN) sending a plurality of sets of encoded data slices to DSN memory for storage in accordance with a plurality of sets of DSN data addresses. The method continues with the DS processing module generating retrieval data that is based on a data object number and data storage information. The method continues with the DS processing module dispersed storage error encoding the retrieval data to produce a set of encoded retrieval data slices and generating a set of DSN retrieval data addresses based on the data name and on retrieval data storage information. The method continues with the DS processing module sending the set of encoded retrieval data slices to the DSN memory for storage in accordance with the set of DSN retrieval data addresses.

Description

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to 35 U.S.C. § 121 as a divisional of U.S. Utility Application No. 14/307,625, entitled “STORING DATA IN A DIRECTORY-LESS DISPERSED STORAGE NETWORK”, filed Jun. 18, 2014, issuing as U.S. Pat. No. 9,495,118 on Nov. 15, 2016, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 61/860,498, entitled “DISPERSED STORAGE AND COMPUTING NETWORK COMPONENTS AND OPTIMIZATIONS”, filed Jul. 31, 2013, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable

BACKGROUND

Technical Field

This present disclosure relates generally to computer networks and more particularly to dispersed storage of data and distributed task processing of data.

Description of Related Art

Computing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function. For example, Hadoop is an open source software framework that supports distributed applications enabling application execution by thousands of computers.

In addition to cloud computing, a computer may use “cloud storage” as part of its memory system. As is known, cloud storage enables a user, via its computer, to store files, applications, etc. on an Internet storage system. The Internet storage system may include a RAID (redundant array of independent disks) system and/or a dispersed storage system that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributed computing system in accordance with the present disclosure;

FIG. 2 is a schematic block diagram of an embodiment of a computing core in accordance with the present disclosure;

FIG. 3 is a diagram of an example of a distributed storage and task processing in accordance with the present disclosure;

FIG. 4 is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST) processing in accordance with the present disclosure;

FIG. 5 is a logic diagram of an example of a method for outbound DST processing in accordance with the present disclosure;

FIG. 6 is a schematic block diagram of an embodiment of a dispersed error encoding in accordance with the present disclosure;

FIG. 7 is a diagram of an example of a segment processing of the dispersed error encoding in accordance with the present disclosure;

FIG. 8 is a diagram of an example of error encoding and slicing processing of the dispersed error encoding in accordance with the present disclosure;

FIG. 9 is a diagram of an example of grouping selection processing of the outbound DST processing in accordance with the present disclosure;

FIG. 10 is a diagram of an example of converting data into slice groups in accordance with the present disclosure;

FIG. 11 is a schematic block diagram of an embodiment of a DST execution unit in accordance with the present disclosure;

FIG. 12 is a schematic block diagram of an example of operation of a DST execution unit in accordance with the present disclosure;

FIG. 13 is a schematic block diagram of an embodiment of an inbound distributed storage and/or task (DST) processing in accordance with the present disclosure;

FIG. 14 is a logic diagram of an example of a method for inbound DST processing in accordance with the present disclosure;

FIG. 15 is a diagram of an example of de-grouping selection processing of the inbound DST processing in accordance with the present disclosure;

FIG. 16 is a schematic block diagram of an embodiment of a dispersed error decoding in accordance with the present disclosure;

FIG. 17 is a diagram of an example of de-slicing and error decoding processing of the dispersed error decoding in accordance with the present disclosure;

FIG. 18 is a diagram of an example of a de-segment processing of the dispersed error decoding in accordance with the present disclosure;

FIG. 19 is a diagram of an example of converting slice groups into data in accordance with the present disclosure;

FIG. 20 is a diagram of an example of a distributed storage within the distributed computing system in accordance with the present disclosure;

FIG. 21 is a schematic block diagram of an example of operation of outbound distributed storage and/or task (DST) processing for storing data in accordance with the present disclosure;

FIG. 22 is a schematic block diagram of an example of a dispersed error encoding for the example ofFIG. 21 in accordance with the present disclosure;

FIG. 23 is a diagram of an example of converting data into pillar slice groups for storage in accordance with the present disclosure;

FIG. 24 is a schematic block diagram of an example of a storage operation of a DST execution unit in accordance with the present disclosure;

FIG. 25 is a schematic block diagram of an example of operation of inbound distributed storage and/or task (DST) processing for retrieving dispersed error encoded data in accordance with the present disclosure;

FIG. 26 is a schematic block diagram of an example of a dispersed error decoding for the example ofFIG. 25 in accordance with the present disclosure;

FIG. 27 is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing a plurality of data and a plurality of task codes in accordance with the present disclosure;

FIG. 28 is a schematic block diagram of an example of the distributed computing system performing tasks on stored data in accordance with the present disclosure;

FIG. 29 is a schematic block diagram of an embodiment of a task distribution module facilitating the example ofFIG. 28 in accordance with the present disclosure;

FIG. 30 is a diagram of a specific example of the distributed computing system performing tasks on stored data in accordance with the present disclosure;

FIG. 31 is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing data and task codes for the example ofFIG. 30 in accordance with the present disclosure;

FIG. 32 is a diagram of an example of DST allocation information for the example ofFIG. 30 in accordance with the present disclosure;

FIGS. 33-38 are schematic block diagrams of the DSTN module performing the example ofFIG. 30 in accordance with the present disclosure;

FIG. 39 is a diagram of an example of combining result information into final results for the example ofFIG. 30 in accordance with the present disclosure;

FIGS. 40A-40D are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of storing data in DSN memory in accordance with the present disclosure;

FIG. 40E is a flowchart illustrating an example of accessing data in accordance with the present disclosure;

FIG. 41 is a flowchart illustrating an example of updating a dispersed storage network (DSN) address in accordance with the present disclosure;

FIG. 42 is a flowchart illustrating an example of accessing an encoded data slice in accordance with the present disclosure;

FIGS. 43A, 43C-F are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of time-based storage of data in accordance with the present disclosure;

FIG. 43B is a timing diagram illustrating an example of generating a time-availability pattern in accordance with the present disclosure;

FIG. 43G is a flowchart illustrating an example of time-based storage of data in accordance with the present disclosure;

FIG. 44A is a schematic block diagram of another embodiment of a distributed storage and task (DST) execution unit in accordance with the present disclosure;

FIG. 44B is a flowchart illustrating an example of assigning resources in accordance with the present disclosure;

FIG. 45A is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system in accordance with the present disclosure;

FIG. 45B is a diagram illustrating an example of load-balancing in accordance with the present disclosure;

FIG. 46A is a schematic block diagram of another embodiment of a distributed storage and task (DST) execution unit in accordance with the present disclosure;

FIG. 46B is a diagram illustrating an example of memory utilization in accordance with the present disclosure;

FIG. 46C is a diagram illustrating another example of memory utilization in accordance with the present disclosure;

FIG. 46D is a flowchart illustrating an example of updating memory utilization information in accordance with the present disclosure;

FIG. 46E is a flowchart illustrating example ways to identify slices needing a rebuild in accordance with the present disclosure;

FIG. 46F is a flowchart illustrating another example of updating memory utilization information;

FIG. 46G is a schematic block diagram illustrating an example DST client module structure for memory utilization;

FIG. 47A is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system in accordance with the present disclosure;

FIG. 47B is a diagram illustrating an example of generating a slice name in accordance with the present disclosure;

FIG. 47C is a flowchart illustrating an example of co-locating storage of data in accordance with the present disclosure;

FIG. 47D is a flowchart illustrating one example of obtaining the plurality of sets of encoded data slices to be co-located; and

FIG. 47E is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system in accordance with the present disclosure.

DETAILED DESCRIPTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system10 that includes auser device12 and/or auser device14, a distributed storage and/or task (DST)processing unit16, a distributed storage and/or task network (DSTN) managingunit18, a DSTintegrity processing unit20, and a distributed storage and/or task network (DSTN)module22. The components of the distributedcomputing system10 are coupled via anetwork24, which may include one or more wireless and/or wire lined communication systems; one or more private intranet systems and/or public internet systems; and/or one or more local area networks (LAN) and/or wide area networks (WAN).

TheDSTN module22 includes a plurality of distributed storage and/or task (DST)execution units36 that may be located at geographically different sites (e.g., one in Chicago, one in Milwaukee, etc.). Each of the DST execution units is operable to store dispersed error encoded data and/or to execute, in a distributed manner, one or more tasks on data. The tasks may be a simple function (e.g., a mathematical function, a logic function, an identify function, a find function, a search engine function, a replace function, etc.), a complex function (e.g., compression, human and/or computer language translation, text-to-voice conversion, voice-to-text conversion, etc.), multiple simple and/or complex functions, one or more algorithms, one or more applications, etc.

Each of the user devices12-14, theDST processing unit16, theDSTN managing unit18, and the DSTintegrity processing unit20 include acomputing core26 and may be a portable computing device and/or a fixed computing device. A portable computing device may be a social networking device, a gaming device, a cell phone, a smart phone, a personal digital assistant, a digital music player, a digital video player, a laptop computer, a handheld computer, a tablet, a video game controller, and/or any other portable device that includes a computing core. A fixed computing device may be a personal computer (PC), a computer server, a cable set-top box, a satellite receiver, a television set, a printer, a fax machine, home entertainment equipment, a video game console, and/or any type of home or office computing equipment.User device12 andDST processing unit16 are configured to include aDST client module34.

With respect to interfaces, eachinterface30,32, and33 includes software and/or hardware to support one or more communication links via thenetwork24 indirectly and/or directly. For example,interface30 supports a communication link (e.g., wired, wireless, direct, via a LAN, via thenetwork24, etc.) betweenuser device14 and theDST processing unit16. As another example,interface32 supports communication links (e.g., a wired connection, a wireless connection, a LAN connection, and/or any other type of connection to/from the network24) betweenuser device12 and theDSTN module22 and between theDST processing unit16 and theDSTN module22. As yet another example,interface33 supports a communication link for each of theDSTN managing unit18 and DSTintegrity processing unit20 to thenetwork24.

The distributedcomputing system10 is operable to support dispersed storage (DS) error encoded data storage and retrieval, to support distributed task processing on received data, and/or to support distributed task processing on stored data. In general, and with respect to DS error encoded data storage and retrieval, the distributedcomputing system10 supports three primary operations: storage management, data storage and retrieval (an example of which will be discussed with reference toFIGS. 20-26), and data storage integrity verification. In accordance with these three primary functions, data can be encoded, distributedly stored in physically different locations, and subsequently retrieved in a reliable and secure manner. Such a system is tolerant of a significant number of failures (e.g., up to a failure level, which may be greater than or equal to a pillar width minus a decode threshold minus one) that may result from individual storage device failures and/or network equipment failures without loss of data and without the need for a redundant or backup copy. Further, the system allows the data to be stored for an indefinite period of time without data loss and does so in a secure manner (e.g., the system is very resistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage and retrieval) begins and ends with a user device12-14. For instance, if a second type ofuser device14 hasdata40 to store in theDSTN module22, it sends thedata40 to theDST processing unit16 via itsinterface30. Theinterface30 functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). In addition, theinterface30 may attach a user identification code (ID) to thedata40.

To support storage management, theDSTN managing unit18 performs DS management services. One such DS management service includes theDSTN managing unit18 establishing distributed data storage parameters (e.g., vault creation, distributed storage parameters, security parameters, billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example, theDSTN managing unit18 coordinates creation of a vault (e.g., a virtual memory block) within memory of theDSTN module22 for a user device, a group of devices, or for public access and establishes per vault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit18 may facilitate storage of DS error encoding parameters for each vault of a plurality of vaults by updating registry information for the distributedcomputing system10. The facilitating includes storing updated registry information in one or more of theDSTN module22, theuser device12, theDST processing unit16, and the DSTintegrity processing unit20.

The DS error encoding parameters (e.g., or dispersed storage error coding parameters) include data segmenting information (e.g., how many segments data (e.g., a file, a group of files, a data block, etc.) is divided into), segment security information (e.g., per segment encryption, compression, integrity checksum, etc.), error coding information (e.g., pillar width, decode threshold, read threshold, write threshold, etc.), slicing information (e.g., the number of encoded data slices that will be created for each data segment); and slice security information (e.g., per encoded data slice encryption, compression, integrity checksum, etc.).

TheDSTN managing unit18 creates and stores user profile information (e.g., an access control list (ACL)) in local memory and/or within memory of theDSTN module22. The user profile information includes authentication information, permissions, and/or the security parameters. The security parameters may include encryption/decryption scheme, one or more encryption keys, key generation scheme, and/or data encoding/decoding scheme.

TheDSTN managing unit18 creates billing information for a particular user, a user group, a vault access, public vault access, etc. For instance, theDSTN managing unit18 tracks the number of times a user accesses a private vault and/or public vaults, which can be used to generate a per-access billing information. In another instance, theDSTN managing unit18 tracks the amount of data stored and/or retrieved by a user device and/or a user group, which can be used to generate a per-data-amount billing information.

Another DS management service includes theDSTN managing unit18 performing network operations, network administration, and/or network maintenance. Network operations includes authenticating user data allocation requests (e.g., read and/or write requests), managing creation of vaults, establishing authentication credentials for user devices, adding/deleting components (e.g., user devices, DST execution units, and/or DST processing units) from the distributedcomputing system10, and/or establishing authentication credentials forDST execution units36. Network administration includes monitoring devices and/or units for failures, maintaining vault information, determining device and/or unit activation status, determining device and/or unit loading, and/or determining any other system level operation that affects the performance level of thesystem10. Network maintenance includes facilitating replacing, upgrading, repairing, and/or expanding a device and/or unit of thesystem10.

To support data storage integrity verification within the distributedcomputing system10, the DSTintegrity processing unit20 performs rebuilding of ‘bad’ or missing encoded data slices. At a high level, the DSTintegrity processing unit20 performs rebuilding by periodically attempting to retrieve/list encoded data slices, and/or slice names of the encoded data slices, from theDSTN module22. For retrieved encoded slices, they are checked for errors due to data corruption, outdated version, etc. If a slice includes an error, it is flagged as a ‘bad’ slice. For encoded data slices that were not received and/or not listed, they are flagged as missing slices. Bad and/or missing slices are subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices to produce rebuilt slices. The rebuilt slices are stored in memory of theDSTN module22. Note that the DSTintegrity processing unit20 may be a separate unit as shown, it may be included in theDSTN module22, it may be included in theDST processing unit16, and/or distributed among theDST execution units36.

To support distributed task processing on received data, the distributedcomputing system10 has two primary operations: DST (distributed storage and/or task processing) management and DST execution on received data (an example of which will be discussed with reference toFIGS. 3-19). With respect to the storage portion of the DST management, theDSTN managing unit18 functions as previously described. With respect to the tasking processing of the DST management, theDSTN managing unit18 performs distributed task processing (DTP) management services. One such DTP management service includes theDSTN managing unit18 establishing DTP parameters (e.g., user-vault affiliation information, billing information, user-task information, etc.) for a user device12-14 individually or as part of a group of user devices.

Another DTP management service includes theDSTN managing unit18 performing DTP network operations, network administration (which is essentially the same as described above), and/or network maintenance (which is essentially the same as described above). Network operations include, but are not limited to, authenticating user task processing requests (e.g., valid request, valid user, etc.), authenticating results and/or partial results, establishing DTP authentication credentials for user devices, adding/deleting components (e.g., user devices, DST execution units, and/or DST processing units) from the distributed computing system, and/or establishing DTP authentication credentials for DST execution units.

To support distributed task processing on stored data, the distributedcomputing system10 has two primary operations: DST (distributed storage and/or task) management and DST execution on stored data. With respect to the DST execution on stored data, if the second type ofuser device14 has atask request38 for execution by theDSTN module22, it sends thetask request38 to theDST processing unit16 via itsinterface30. An example of DST execution on stored data will be discussed in greater detail with reference toFIGS. 27-39. With respect to the DST management, it is substantially similar to the DST management to support distributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of acomputing core26 that includes aprocessing module50, amemory controller52,main memory54, a videographics processing unit55, an input/output (IO)controller56, a peripheral component interconnect (PCI)interface58, anIO interface module60, at least one IOdevice interface module62, a read only memory (ROM) basic input output system (BIOS)64, and one or more memory interface modules. The one or more memory interface module(s) includes one or more of a universal serial bus (USB) interface module66, a host bus adapter (HBA)interface module68, anetwork interface module70, aflash interface module72, a harddrive interface module74, and aDSTN interface module76.

TheDSTN interface module76 functions to mimic a conventional operating system (OS) file system interface (e.g., network file system (NFS), flash file system (FFS), disk file system (DFS), file transfer protocol (FTP), web-based distributed authoring and versioning (WebDAV), etc.) and/or a block memory interface (e.g., small computer system interface (SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module76 and/or thenetwork interface module70 may function as theinterface30 of theuser device14 ofFIG. 1. Further note that the IOdevice interface module62 and/or the memory interface modules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing system performing a distributed storage and task processing operation. The distributed computing system includes a DST (distributed storage and/or task) client module34 (which may be inuser device14 and/or inDST processing unit16 ofFIG. 1), anetwork24, a plurality of DST execution units1-n that includes two or moreDST execution units36 ofFIG. 1 (which form at least a portion ofDSTN module22 ofFIG. 1), a DST managing module (not shown), and a DST integrity verification module (not shown). TheDST client module34 includes an outboundDST processing section80 and an inboundDST processing section82. Each of the DST execution units1-n includes acontroller86, aprocessing module84,memory88, a DT (distributed task)execution module90, and aDST client module34.

In an example of operation, theDST client module34 receivesdata92 and one ormore tasks94 to be performed upon thedata92. Thedata92 may be of any size and of any content, where, due to the size (e.g., greater than a few Terabytes), the content (e.g., secure data, etc.), and/or task(s) (e.g., MIPS intensive), distributed processing of the task(s) on the data is desired. For example, thedata92 may be one or more digital books, a copy of a company's emails, a large-scale Internet search, a video security file, one or more entertainment video files (e.g., television programs, movies, etc.), data files, and/or any other large amount of data (e.g., greater than a few Terabytes).

Within theDST client module34, the outboundDST processing section80 receives thedata92 and the task(s)94. The outboundDST processing section80 processes thedata92 to produceslice groupings96. As an example of such processing, the outboundDST processing section80 partitions thedata92 into a plurality of data partitions. For each data partition, the outboundDST processing section80 dispersed storage (DS) error encodes the data partition to produce encoded data slices and groups the encoded data slices into aslice grouping96. In addition, the outboundDST processing section80 partitions thetask94 intopartial tasks98, where the number ofpartial tasks98 may correspond to the number ofslice groupings96.

The outboundDST processing section80 then sends, via thenetwork24, theslice groupings96 and thepartial tasks98 to the DST execution units1-n of theDSTN module22 ofFIG. 1. For example, the outboundDST processing section80 sendsslice group1 andpartial task1 toDST execution unit1. As another example, the outboundDST processing section80 sends slice group #n and partial task #n to DST execution unit #n.

Each DST execution unit performs itspartial task98 upon itsslice group96 to producepartial results102. For example, DSTexecution unit #1 performspartial task #1 onslice group #1 to produce apartial result #1, for results. As a more specific example,slice group #1 corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recording where the phrase is found, and establishing a phrase count. In this more specific example, thepartial result #1 includes information as to where the phrase was found and includes the phrase count.

Upon completion of generating their respectivepartial results102, the DST execution units send, via thenetwork24, theirpartial results102 to the inboundDST processing section82 of theDST client module34. The inboundDST processing section82 processes the receivedpartial results102 to produce aresult104. Continuing with the specific example of the preceding paragraph, the inboundDST processing section82 combines the phrase count from each of theDST execution units36 to produce a total phrase count. In addition, the inboundDST processing section82 combines the ‘where the phrase was found’ information from each of theDST execution units36 within their respective data partitions to produce ‘where the phrase was found’ information for the series of digital books.

In another example of operation, theDST client module34 requests retrieval of stored data within the memory of the DST execution units36 (e.g., memory of the DSTN module). In this example, thetask94 is retrieve data stored in the memory of the DSTN module. Accordingly, the outboundDST processing section80 converts thetask94 into a plurality ofpartial tasks98 and sends thepartial tasks98 to the respective DST execution units1-n.

In response to thepartial task98 of retrieving stored data, aDST execution unit36 identifies the corresponding encoded data slices100 and retrieves them. For example, DSTexecution unit #1 receivespartial task #1 and retrieves, in response thereto, retrievedslices #1. TheDST execution units36 send their respective retrievedslices100 to the inboundDST processing section82 via thenetwork24.

The inboundDST processing section82 converts the retrievedslices100 intodata92. For example, the inboundDST processing section82 de-groups the retrievedslices100 to produce encoded slices per data partition. The inboundDST processing section82 then DS error decodes the encoded slices per data partition to produce data partitions. The inboundDST processing section82 de-partitions the data partitions to recapture thedata92.

FIG. 4 is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST)processing section80 of aDST client module34FIG. 1 coupled to aDSTN module22 of aFIG. 1 (e.g., a plurality of n DST execution units36) via anetwork24. The outboundDST processing section80 includes adata partitioning module110, a dispersed storage (DS)error encoding module112, agrouping selector module114, acontrol module116, and a distributedtask control module118.

In an example of operation, thedata partitioning module110partitions data92 into a plurality ofdata partitions120. The number of partitions and the size of the partitions may be selected by thecontrol module116 viacontrol160 based on the data92 (e.g., its size, its content, etc.), a correspondingtask94 to be performed (e.g., simple, complex, single step, multiple steps, etc.), DS encoding parameters (e.g., pillar width, decode threshold, write threshold, segment security parameters, slice security parameters, etc.), capabilities of the DST execution units36 (e.g., processing resources, availability of processing recourses, etc.), and/or as may be inputted by a user, system administrator, or other operator (human or automated). For example, thedata partitioning module110 partitions the data92 (e.g., 100 Terabytes) into 100,000 data segments, each being 1 Gigabyte in size. Alternatively, thedata partitioning module110 partitions thedata92 into a plurality of data segments, where some of data segments are of a different size, are of the same size, or a combination thereof.

The DSerror encoding module112 receives thedata partitions120 in a serial manner, a parallel manner, and/or a combination thereof. For eachdata partition120, the DSerror encoding module112 DS error encodes thedata partition120 in accordance withcontrol information160 from thecontrol module116 to produce encoded data slices122. The DS error encoding includes segmenting the data partition into data segments, segment security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC), etc.), error encoding, slicing, and/or per slice security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information160 indicates which steps of the DS error encoding are active for a given data partition and, for active steps, indicates the parameters for the step. For example, thecontrol information160 indicates that the error encoding is active and includes error encoding parameters (e.g., pillar width, decode threshold, write threshold, read threshold, type of error encoding, etc.).

Thegrouping selector module114 groups the encodedslices122 of a data partition into a set ofslice groupings96. The number of slice groupings corresponds to the number ofDST execution units36 identified for aparticular task94. For example, if fiveDST execution units36 are identified for theparticular task94, the grouping selector module groups the encodedslices122 of a data partition into fiveslice groupings96. Thegrouping selector module114 outputs theslice groupings96 to the correspondingDST execution units36 via thenetwork24.

The distributedtask control module118 receives thetask94 and converts thetask94 into a set ofpartial tasks98. For example, the distributedtask control module118 receives a task to find where in the data (e.g., a series of books) a phrase occurs and a total count of the phrase usage in the data. In this example, the distributedtask control module118 replicates thetask94 for eachDST execution unit36 to produce thepartial tasks98. In another example, the distributedtask control module118 receives a task to find where in the data a first phrase occurs, where in the data a second phrase occurs, and a total count for each phrase usage in the data. In this example, the distributedtask control module118 generates a first set ofpartial tasks98 for finding and counting the first phrase and a second set of partial tasks for finding and counting the second phrase. The distributedtask control module118 sends respective first and/or secondpartial tasks98 to eachDST execution unit36.

FIG. 5 is a logic diagram of an example of a method for outbound distributed storage and task (DST) processing that begins atstep126 where a DST client module receives data and one or more corresponding tasks. The method continues atstep128 where the DST client module determines a number of DST units to support the task for one or more data partitions. For example, the DST client module may determine the number of DST units to support the task based on the size of the data, the requested task, the content of the data, a predetermined number (e.g., user indicated, system administrator determined, etc.), available DST units, capability of the DST units, and/or any other factor regarding distributed task processing of the data. The DST client module may select the same DST units for each data partition, may select different DST units for the data partitions, or a combination thereof.

The method continues atstep130 where the DST client module determines processing parameters of the data based on the number of DST units selected for distributed task processing. The processing parameters include data partitioning information, DS encoding parameters, and/or slice grouping information. The data partitioning information includes a number of data partitions, size of each data partition, and/or organization of the data partitions (e.g., number of data blocks in a partition, the size of the data blocks, and arrangement of the data blocks). The DS encoding parameters include segmenting information, segment security information, error encoding information (e.g., dispersed storage error encoding function parameters including one or more of pillar width, decode threshold, write threshold, read threshold, generator matrix), slicing information, and/or per slice security information. The slice grouping information includes information regarding how to arrange the encoded data slices into groups for the selected DST units. As a specific example, if the DST client module determines that five DST units are needed to support the task, then it determines that the error encoding parameters include a pillar width of five and a decode threshold of three.

The method continues atstep132 where the DST client module determines task partitioning information (e.g., how to partition the tasks) based on the selected DST units and data processing parameters. The data processing parameters include the processing parameters and DST unit capability information. The DST unit capability information includes the number of DT (distributed task) execution units, execution capabilities of each DT execution unit (e.g., MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, memory information (e.g., type, size, availability, etc.)), and/or any information germane to executing one or more tasks.

The method continues atstep134 where the DST client module processes the data in accordance with the processing parameters to produce slice groupings. The method continues atstep136 where the DST client module partitions the task based on the task partitioning information to produce a set of partial tasks. The method continues atstep138 where the DST client module sends the slice groupings and the corresponding partial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersed storage (DS)error encoding module112 of an outbound distributed storage and task (DST) processing section. The DSerror encoding module112 includes asegment processing module142, a segmentsecurity processing module144, anerror encoding module146, aslicing module148, and a per slicesecurity processing module150. Each of these modules is coupled to acontrol module116 to receivecontrol information160 therefrom.

In an example of operation, thesegment processing module142 receives adata partition120 from a data partitioning module and receives segmenting information as thecontrol information160 from thecontrol module116. The segmenting information indicates how thesegment processing module142 is to segment thedata partition120. For example, the segmenting information indicates how many rows to segment the data based on a decode threshold of an error encoding scheme, indicates how many columns to segment the data into based on a number and size of data blocks within thedata partition120, and indicates how many columns to include in adata segment152. Thesegment processing module142 segments thedata120 intodata segments152 in accordance with the segmenting information.

The segmentsecurity processing module144, when enabled by thecontrol module116, secures thedata segments152 based on segment security information received ascontrol information160 from thecontrol module116. The segment security information includes data compression, encryption, watermarking, integrity check (e.g., cyclic redundancy check (CRC), etc.), and/or any other type of digital security. For example, when the segmentsecurity processing module144 is enabled, it may compress adata segment152, encrypt the compressed data segment, and generate a CRC value for the encrypted data segment to produce asecure data segment154. When the segmentsecurity processing module144 is not enabled, it passes thedata segments152 to theerror encoding module146 or is bypassed such that thedata segments152 are provided to theerror encoding module146.

Theerror encoding module146 encodes thesecure data segments154 in accordance with error correction encoding parameters received ascontrol information160 from thecontrol module116. The error correction encoding parameters (e.g., also referred to as dispersed storage error coding parameters) include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an online coding algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction encoding parameters identify a specific error correction encoding scheme, specifies a pillar width of five, and specifies a decode threshold of three. From these parameters, theerror encoding module146 encodes adata segment154 to produce an encodeddata segment156.

Theslicing module148 slices the encodeddata segment156 in accordance with the pillar width of the error correction encoding parameters received ascontrol information160. For example, if the pillar width is five, theslicing module148 slices an encodeddata segment156 into a set of five encoded data slices. As such, for a plurality of encodeddata segments156 for a given data partition, the slicing module outputs a plurality of sets of encoded data slices158.

The per slicesecurity processing module150, when enabled by thecontrol module116, secures each encodeddata slice158 based on slice security information received ascontrol information160 from thecontrol module116. The slice security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the per slicesecurity processing module150 is enabled, it compresses an encodeddata slice158, encrypts the compressed encoded data slice, and generates a CRC value for the encrypted encoded data slice to produce a secure encodeddata slice122. When the per slicesecurity processing module150 is not enabled, it passes the encoded data slices158 or is bypassed such that the encoded data slices158 are the output of the DSerror encoding module112. Note that thecontrol module116 may be omitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersed storage (DS) error encoding module. In this example, asegment processing module142 receives adata partition120 that includes 45 data blocks (e.g., d1-d45), receives segmenting information (i.e., control information160) from a control module, and segments thedata partition120 in accordance with thecontrol information160 to producedata segments152. Each data block may be of the same size as other data blocks or of a different size. In addition, the size of each data block may be a few bytes to megabytes of data. As previously mentioned, the segmenting information indicates how many rows to segment the data partition into, indicates how many columns to segment the data partition into, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme is three; as such the number of rows to divide the data partition into is three. The number of columns for each row is set to 15, which is based on the number and size of data blocks. The data blocks of the data partition are arranged in rows and columns in a sequential order (i.e., the first row includes the first 15 data blocks; the second row includes the second 15 data blocks; and the third row includes the last 15 data blocks).

With the data blocks arranged into the desired sequential order, they are divided into data segments based on the segmenting information. In this example, the data partition is divided into 8 data segments; the first 7 include 2 columns of three rows and the last includes 1 column of three rows. Note that the first row of the 8 data segments is in sequential order of the first 15 data blocks; the second row of the 8 data segments in sequential order of the second 15 data blocks; and the third row of the 8 data segments in sequential order of the last 15 data blocks. Note that the number of data blocks, the grouping of the data blocks into segments, and size of the data blocks may vary to accommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicing processing of the dispersed error encoding processing the data segments ofFIG. 7. In this example,data segment1 includes 3 rows with each row being treated as one word for encoding. As such,data segment1 includes three words for encoding:word1 including data blocks d1 and d2,word2 including data blocks d16 and d17, andword3 including data blocks d31 and d32. Each of data segments2-7 includes three words where each word includes two data blocks.Data segment8 includes three words where each word includes a single data block (e.g., d15, d30, and d45).

In operation, anerror encoding module146 and aslicing module148 convert each data segment into a set of encoded data slices in accordance with error correction encoding parameters ascontrol information160. More specifically, when the error correction encoding parameters indicate a unity matrix Reed-Solomon based encoding algorithm, 5 pillars, and decode threshold of 3, the first three encoded data slices of the set of encoded data slices for a data segment are substantially similar to the corresponding word of the data segment. For instance, when the unity matrix Reed-Solomon based encoding algorithm is applied todata segment1, the content of the first encoded data slice (DS1_d1&2) of the first set of encoded data slices (e.g., corresponding to data segment1) is substantially similar to content of the first word (e.g., d1 & d2); the content of the second encoded data slice (DS1_d16&17) of the first set of encoded data slices is substantially similar to content of the second word (e.g., d16 & d17); and the content of the third encoded data slice (DS1_d31&32) of the first set of encoded data slices is substantially similar to content of the third word (e.g., d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 and ES1_2) of the first set of encoded data slices include error correction data based on the first-third words of the first data segment. With such an encoding and slicing scheme, retrieving any three of the five encoded data slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments2-7 yield sets of encoded data slices similar to the set of encoded data slices ofdata segment1. For instance, the content of the first encoded data slice (DS2_d3&4) of the second set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 & d4); the content of the second encoded data slice (DS2_d18&19) of the second set of encoded data slices is substantially similar to content of the second word (e.g., d18 & d19); and the content of the third encoded data slice (DS2_d33&34) of the second set of encoded data slices is substantially similar to content of the third word (e.g., d33 & d34). The content of the fourth and fifth encoded data slices (e.g., ES1_1 and ES1_2) of the second set of encoded data slices includes error correction data based on the first-third words of the second data segment.

FIG. 9 is a diagram of an example of grouping selection processing of an outbound distributed storage and task (DST) processing in accordance with group selection information ascontrol information160 from a control module. Encoded slices fordata partition122 are grouped in accordance with thecontrol information160 to produceslice groupings96. In this example, agrouping selector module114 organizes the encoded data slices into five slice groupings (e.g., one for each DST execution unit of a distributed storage and task network (DSTN) module). As a specific example, thegrouping selector module114 creates a first slice grouping for a DSTexecution unit #1, which includes first encoded slices of each of the sets of encoded slices. As such, the first DST execution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

Thegrouping selector module114 also creates a second slice grouping for a DSTexecution unit #2, which includes second encoded slices of each of the sets of encoded slices. As such, the second DST execution unit receives encoded data slices corresponding to data blocks16-30. Thegrouping selector module114 further creates a third slice grouping for DSTexecution unit #3, which includes third encoded slices of each of the sets of encoded slices. As such, the third DST execution unit receives encoded data slices corresponding to data blocks31-45.

Thegrouping selector module114 creates a fourth slice grouping for DSTexecution unit #4, which includes fourth encoded slices of each of the sets of encoded slices. As such, the fourth DST execution unit receives encoded data slices corresponding to first error encoding information (e.g., encoded data slices of error coding (EC) data). Thegrouping selector module114 further creates a fifth slice grouping for DSTexecution unit #5, which includes fifth encoded slices of each of the sets of encoded slices. As such, the fifth DST execution unit receives encoded data slices corresponding to second error encoding information.

FIG. 10 is a diagram of an example of convertingdata92 into slice groups that expands on the preceding figures. As shown, thedata92 is partitioned in accordance with apartitioning function164 into a plurality of data partitions (1-x, where x is an integer greater than 4). Each data partition (or chunkset of data) is encoded and grouped into slice groupings as previously discussed by an encoding andgrouping function166. For a given data partition, the slice groupings are sent to distributed storage and task (DST) execution units. From data partition to data partition, the ordering of the slice groupings to the DST execution units may vary.

For example, the slice groupings ofdata partition #1 is sent to the DST execution units such that the first DST execution receives first encoded data slices of each of the sets of encoded data slices, which corresponds to a first continuous data chunk of the first data partition (e.g., refer toFIG. 9), a second DST execution receives second encoded data slices of each of the sets of encoded data slices, which corresponds to a second continuous data chunk of the first data partition, etc.

For the second data partition, the slice groupings may be sent to the DST execution units in a different order than it was done for the first data partition. For instance, the first slice grouping of the second data partition (e.g., slice group2_1) is sent to the second DST execution unit; the second slice grouping of the second data partition (e.g., slice group2_2) is sent to the third DST execution unit; the third slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice grouping of the second data partition (e.g., slice group2_4, which includes first error coding information) is sent to the fifth DST execution unit; and the fifth slice grouping of the second data partition (e.g., slice group2_5, which includes second error coding information) is sent to the first DST execution unit.

The pattern of sending the slice groupings to the set of DST execution units may vary in a predicted pattern, a random pattern, and/or a combination thereof from data partition to data partition. In addition, from data partition to data partition, the set of DST execution units may change. For example, for the first data partition, DST execution units1-5 may be used; for the second data partition, DST execution units6-10 may be used; for the third data partition, DST execution units3-7 may be used; etc. As is also shown, the task is divided into partial tasks that are sent to the DST execution units in conjunction with the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST (distributed storage and/or task) execution unit that includes aninterface169, acontroller86,memory88, one or more DT (distributed task)execution modules90, and aDST client module34. Thememory88 is of sufficient size to store a significant number of encoded data slices (e.g., thousands of slices to hundreds-of-millions of slices) and may include one or more hard drives and/or one or more solid-state memory devices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution module receives a slice grouping96 (e.g., slice group #1) viainterface169. Theslice grouping96 includes, per partition, encoded data slices of contiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices of contiguous data forpartitions #1 and #x (and potentially others between 3 and x) and receives encoded data slices of EC data forpartitions #2 and #3 (and potentially others between 3 and x). Examples of encoded data slices of contiguous data and encoded data slices of error coding (EC) data are discussed with reference toFIG. 9. Thememory88 stores the encoded data slices ofslice groupings96 in accordance withmemory control information174 it receives from thecontroller86.

The controller86 (e.g., a processing module, a CPU, etc.) generates thememory control information174 based on a partial task(s)98 and distributed computing information (e.g., user information (e.g., user ID, distributed computing permissions, data access permission, etc.), vault information (e.g., virtual memory assigned to user, user group, temporary storage for task processing, etc.), task validation information, etc.). For example, thecontroller86 interprets the partial task(s)98 in light of the distributed computing information to determine whether a requestor is authorized to perform thetask98, is authorized to access the data, and/or is authorized to perform the task on this particular data. When the requestor is authorized, thecontroller86 determines, based on thetask98 and/or another input, whether the encoded data slices of theslice grouping96 are to be temporarily stored or permanently stored. Based on the foregoing, thecontroller86 generates thememory control information174 to write the encoded data slices of theslice grouping96 into thememory88 and to indicate whether theslice grouping96 is permanently stored or temporarily stored.

With theslice grouping96 stored in thememory88, thecontroller86 facilitates execution of the partial task(s)98. In an example, thecontroller86 interprets thepartial task98 in light of the capabilities of the DT execution module(s)90. The capabilities include one or more of MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, etc. If thecontroller86 determines that the DT execution module(s)90 have sufficient capabilities, it generatestask control information176.

The task controlinformation176 may be a generic instruction (e.g., perform the task on the stored slice grouping) or a series of operational codes. In the former instance, theDT execution module90 includes a co-processor function specifically configured (fixed or programmed) to perform the desiredtask98. In the latter instance, theDT execution module90 includes a general processor topology where the controller stores an algorithm corresponding to theparticular task98. In this instance, thecontroller86 provides the operational codes (e.g., assembly language, source code of a programming language, object code, etc.) of the algorithm to theDT execution module90 for execution.

Depending on the nature of thetask98, theDT execution module90 may generate intermediatepartial results102 that are stored in thememory88 or in a cache memory (not shown) within theDT execution module90. In either case, when theDT execution module90 completes execution of thepartial task98, it outputs one or morepartial results102. Thepartial results102 may also be stored inmemory88.

If, when thecontroller86 is interpreting whether capabilities of the DT execution module(s)90 can support thepartial task98, thecontroller86 determines that the DT execution module(s)90 cannot adequately support the task98 (e.g., does not have the right resources, does not have sufficient available resources, available resources would be too slow, etc.), it then determines whether thepartial task98 should be fully offloaded or partially offloaded.

If thecontroller86 determines that thepartial task98 should be fully offloaded, it generatesDST control information178 and provides it to theDST client module34. TheDST control information178 includes thepartial task98, memory storage information regarding theslice grouping96, and distribution instructions. The distribution instructions instruct theDST client module34 to divide thepartial task98 intosub-partial tasks172, to divide theslice grouping96 intosub-slice groupings170, and identify other DST execution units. TheDST client module34 functions in a similar manner as theDST client module34 ofFIGS. 3-10 to produce thesub-partial tasks172 and thesub-slice groupings170 in accordance with the distribution instructions.

TheDST client module34 receives DST feedback168 (e.g., sub-partial results), via theinterface169, from the DST execution units to which the task was offloaded. TheDST client module34 provides the sub-partial results to the DST execution unit, which processes the sub-partial results to produce the partial result(s)102.

If thecontroller86 determines that thepartial task98 should be partially offloaded, it determines what portion of thetask98 and/orslice grouping96 should be processed locally and what should be offloaded. For the portion that is being locally processed, thecontroller86 generatestask control information176 as previously discussed. For the portion that is being offloaded, thecontroller86 generatesDST control information178 as previously discussed.

When theDST client module34 receives DST feedback168 (e.g., sub-partial results) from the DST executions units to which a portion of the task was offloaded, it provides the sub-partial results to theDT execution module90. TheDT execution module90 processes the sub-partial results with the sub-partial results it created to produce the partial result(s)102.

Thememory88 may be further utilized to retrieve one or more of storedslices100, storedresults104,partial results102 when theDT execution module90 storespartial results102 and/orresults104 in thememory88. For example, when thepartial task98 includes a retrieval request, thecontroller86 outputs thememory control174 to thememory88 to facilitate retrieval ofslices100 and/or results104.

FIG. 12 is a schematic block diagram of an example of operation of a distributed storage and task (DST) execution unit storing encoded data slices and executing a task thereon. To store the encoded data slices of apartition1 ofslice grouping1, acontroller86 generates write commands asmemory control information174 such that the encoded slices are stored in desired locations (e.g., permanent or temporary) withinmemory88.

Once the encoded slices are stored, thecontroller86 providestask control information176 to a distributed task (DT)execution module90. As a first step of executing the task in accordance with thetask control information176, theDT execution module90 retrieves the encoded slices frommemory88. TheDT execution module90 then reconstructs contiguous data blocks of a data partition. As shown for this example, reconstructed contiguous data blocks ofdata partition1 include data blocks1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, theDT execution module90 performs the task on the reconstructed contiguous data blocks. For example, the task may be to search the reconstructed contiguous data blocks for a particular word or phrase, identify where in the reconstructed contiguous data blocks the particular word or phrase occurred, and/or count the occurrences of the particular word or phrase on the reconstructed contiguous data blocks. The DST execution unit continues in a similar manner for the encoded data slices of other partitions inslice grouping1. Note that with using the unity matrix error encoding scheme previously discussed, if the encoded data slices of contiguous data are uncorrupted, the decoding of them is a relatively straightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (or missing), it can be rebuilt by accessing other DST execution units that are storing the other encoded data slices of the set of encoded data slices of the corrupted encoded data slice. In this instance, the DST execution unit having the corrupted encoded data slices retrieves at least three encoded data slices (of contiguous data and of error coding data) in the set from the other DST execution units (recall for this example, the pillar width is 5 and the decode threshold is 3). The DST execution unit decodes the retrieved data slices using the DS error encoding parameters to recapture the corresponding data segment. The DST execution unit then re-encodes the data segment using the DS error encoding parameters to rebuild the corrupted encoded data slice. Once the encoded data slice is rebuilt, the DST execution unit functions as previously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbound distributed storage and/or task (DST)processing section82 of a DST client module coupled to DST execution units of a distributed storage and task network (DSTN) module via anetwork24. The inboundDST processing section82 includes ade-grouping module180, a DS (dispersed storage)error decoding module182, adata de-partitioning module184, acontrol module186, and a distributedtask control module188. Note that thecontrol module186 and/or the distributedtask control module188 may be separate modules from corresponding ones of outbound DST processing section or may be the same modules.

In an example of operation, the DST execution units have completed execution of corresponding partial tasks on the corresponding slice groupings to producepartial results102. The inboundDST processing section82 receives thepartial results102 via the distributedtask control module188. The inboundDST processing section82 then processes thepartial results102 to produce a final result, or results104. For example, if the task was to find a specific word or phrase within data, thepartial results102 indicate where in each of the prescribed portions of the data the corresponding DST execution units found the specific word or phrase. The distributedtask control module188 combines the individualpartial results102 for the corresponding portions of the data into afinal result104 for the data as a whole.

In another example of operation, the inboundDST processing section82 is retrieving stored data from the DST execution units (i.e., the DSTN module). In this example, the DST execution units output encoded data slices100 corresponding to the data retrieval requests. Thede-grouping module180 receives retrievedslices100 and de-groups them to produce encoded data slices perdata partition122. The DSerror decoding module182 decodes, in accordance with DS error encoding parameters, the encoded data slices perdata partition122 to producedata partitions120.

The datade-partitioning module184 combines thedata partitions120 into thedata92. Thecontrol module186 controls the conversion of retrievedslices100 into thedata92 usingcontrol signals190 to each of the modules. For instance, thecontrol module186 provides de-grouping information to thede-grouping module180, provides the DS error encoding parameters to the DSerror decoding module182, and provides de-partitioning information to the datade-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executable by distributed storage and task (DST) client module regarding inbound DST processing. The method begins atstep194 where the DST client module receives partial results. The method continues atstep196 where the DST client module retrieves the task corresponding to the partial results. For example, the partial results include header information that identifies the requesting entity, which correlates to the requested task.

The method continues atstep198 where the DST client module determines result processing information based on the task. For example, if the task were to identify a particular word or phrase within the data, the result processing information would indicate to aggregate the partial results for the corresponding portions of the data to produce the final result. As another example, if the task were to count the occurrences of a particular word or phrase within the data, results of processing the information would indicate to add the partial results to produce the final results. The method continues atstep200 where the DST client module processes the partial results in accordance with the result processing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processing of an inbound distributed storage and task (DST) processing section of a DST client module. In general, this is an inverse process of the grouping module of the outbound DST processing section ofFIG. 9. Accordingly, for each data partition (e.g., partition #1), the de-grouping module retrieves the corresponding slice grouping from the DST execution units (EU) (e.g., DST1-5).

As shown, DSTexecution unit #1 provides a first slice grouping, which includes the first encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks1-15); DSTexecution unit #2 provides a second slice grouping, which includes the second encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks16-30); DSTexecution unit #3 provides a third slice grouping, which includes the third encoded slices of each of the sets of encoded slices (e.g., encoded data slices of contiguous data of data blocks31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes the fourth encoded slices of each of the sets of encoded slices (e.g., first encoded data slices of error coding (EC) data); and DSTexecution unit #5 provides a fifth slice grouping, which includes the fifth encoded slices of each of the sets of encoded slices (e.g., first encoded data slices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., received slices100) using ade-grouping selector180 controlled by acontrol signal190 as shown in the example to produce a plurality of sets of encoded data slices (e.g., retrieved slices for a partition into sets of slices122). Each set corresponding to a data segment of the data partition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersed storage (DS)error decoding module182 of an inbound distributed storage and task (DST) processing section. The DSerror decoding module182 includes an inverse per slicesecurity processing module202, ade-slicing module204, anerror decoding module206, an inversesegment security module208, ade-segmenting processing module210, and acontrol module186.

In an example of operation, the inverse per slicesecurity processing module202, when enabled by thecontrol module186, unsecures each encodeddata slice122 based on slice de-security information received as control information190 (e.g., the compliment of the slice security information discussed with reference toFIG. 6) received from thecontrol module186. The slice security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC verification, etc.), and/or any other type of digital security. For example, when the inverse per slicesecurity processing module202 is enabled, it verifies integrity information (e.g., a CRC value) of each encodeddata slice122, it decrypts each verified encoded data slice, and decompresses each decrypted encoded data slice to produce slice encodeddata158. When the inverse per slicesecurity processing module202 is not enabled, it passes the encoded data slices122 as the sliced encodeddata158 or is bypassed such that the retrieved encoded data slices122 are provided as the sliced encodeddata158.

Thede-slicing module204 de-slices the sliced encodeddata158 into encodeddata segments156 in accordance with a pillar width of the error correction encoding parameters received ascontrol information190 from thecontrol module186. For example, if the pillar width is five, thede-slicing module204 de-slices a set of five encoded data slices into an encodeddata segment156. Theerror decoding module206 decodes the encodeddata segments156 in accordance with error correction decoding parameters received ascontrol information190 from thecontrol module186 to producesecure data segments154. The error correction decoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction decoding parameters identify a specific error correction encoding scheme, specify a pillar width of five, and specify a decode threshold of three.

The inverse segmentsecurity processing module208, when enabled by thecontrol module186, unsecures thesecured data segments154 based on segment security information received ascontrol information190 from thecontrol module186. The segment security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC, etc.) verification, and/or any other type of digital security. For example, when the inverse segmentsecurity processing module208 is enabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment154, it decrypts each verified secured data segment, and decompresses each decrypted secure data segment to produce adata segment152. When the inverse segmentsecurity processing module208 is not enabled, it passes the decodeddata segment154 as thedata segment152 or is bypassed.

Thede-segment processing module210 receives thedata segments152 and receives de-segmenting information ascontrol information190 from thecontrol module186. The de-segmenting information indicates how thede-segment processing module210 is to de-segment thedata segments152 into adata partition120. For example, the de-segmenting information indicates how the rows and columns of data segments are to be rearranged to yield thedata partition120.

FIG. 17 is a diagram of an example of de-slicing and error decoding processing of a dispersed error decoding module. Ade-slicing module204 receives at least a decode threshold number of encoded data slices158 for each data segment in accordance withcontrol information190 and provides encodeddata156. In this example, a decode threshold is three. As such, each set of encoded data slices158 is shown to have three encoded data slices per data segment. Thede-slicing module204 may receive three encoded data slices per data segment because an associated distributed storage and task (DST) client module requested retrieving only three encoded data slices per segment or selected three of the retrieved encoded data slices per data segment. As shown, which is based on the unity matrix encoding previously discussed with reference toFIG. 8, an encoded data slice may be a data-based encoded data slice (e.g., DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

Anerror decoding module206 decodes the encodeddata156 of each data segment in accordance with the error correction decoding parameters ofcontrol information190 to produce securedsegments154. In this example,data segment1 includes 3 rows with each row being treated as one word for encoding. As such,data segment1 includes three words:word1 including data blocks d1 and d2,word2 including data blocks d16 and d17, andword3 including data blocks d31 and d32. Each of data segments2-7 includes three words where each word includes two data blocks.Data segment8 includes three words where each word includes a single data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of an inbound distributed storage and task (DST) processing. In this example, ade-segment processing module210 receives data segments152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows and columns in accordance with de-segmenting information ofcontrol information190 to produce adata partition120. Note that the number of rows is based on the decode threshold (e.g., 3 in this specific example) and the number of columns is based on the number and size of the data blocks.

Thede-segmenting module210 converts the rows and columns of data blocks into thedata partition120. Note that each data block may be of the same size as other data blocks or of a different size. In addition, the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups intodata92 within an inbound distributed storage and task (DST) processing section. As shown, thedata92 is reconstructed from a plurality of data partitions (1-x, where x is an integer greater than 4). Each data partition (or chunk set of data) is decoded and re-grouped using a de-grouping anddecoding function212 and ade-partition function214 from slice groupings as previously discussed. For a given data partition, the slice groupings (e.g., at least a decode threshold per data segment of encoded data slices) are received from DST execution units. From data partition to data partition, the ordering of the slice groupings received from the DST execution units may vary as discussed with reference toFIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/or retrieval within the distributed computing system. The distributed computing system includes a plurality of distributed storage and/or task (DST) processing client modules34 (one shown) coupled to a distributed storage and/or task processing network (DSTN) module, or multiple DSTN modules, via anetwork24. TheDST client module34 includes an outboundDST processing section80 and an inboundDST processing section82. The DSTN module includes a plurality of DST execution units. Each DST execution unit includes acontroller86,memory88, one or more distributed task (DT)execution modules90, and aDST client module34.

In an example of data storage, theDST client module34 hasdata92 that it desires to store in the DSTN module. Thedata92 may be a file (e.g., video, audio, text, graphics, etc.), a data object, a data block, an update to a file, an update to a data block, etc. In this instance, the outboundDST processing module80 converts thedata92 into encoded data slices216 as will be further described with reference toFIGS. 21-23. The outboundDST processing module80 sends, via thenetwork24, to the DST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, theDST client module34 issues a retrieve request to the DST execution units for the desireddata92. The retrieve request may address each DST executions units storing encoded data slices of the desired data, address a decode threshold number of DST execution units, address a read threshold number of DST execution units, or address some other number of DST execution units. In response to the request, each addressed DST execution unit retrieves its encoded data slices100 of the desired data and sends them to the inboundDST processing section82, via thenetwork24.

When, for each data segment, the inboundDST processing section82 receives at least a decode threshold number of encoded data slices100, it converts the encoded data slices100 into a data segment. The inboundDST processing section82 aggregates the data segments to produce the retrieveddata92.

FIG. 21 is a schematic block diagram of an embodiment of an outbound distributed storage and/or task (DST)processing section80 of a DST client module coupled to a distributed storage and task network (DSTN) module (e.g., a plurality of DST execution units) via anetwork24. The outboundDST processing section80 includes adata partitioning module110, a dispersed storage (DS)error encoding module112, agrouping selector module114, acontrol module116, and a distributedtask control module118.

In an example of operation, thedata partitioning module110 is by-passed such thatdata92 is provided directly to the DSerror encoding module112. Thecontrol module116 coordinates the by-passing of thedata partitioning module110 by outputting abypass220 message to thedata partitioning module110.

The DSerror encoding module112 receives thedata92 in a serial manner, a parallel manner, and/or a combination thereof. The DSerror encoding module112 DS error encodes the data in accordance withcontrol information160 from thecontrol module116 to produce encoded data slices218. The DS error encoding includes segmenting thedata92 into data segments, segment security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC, etc.)), error encoding, slicing, and/or per slice security processing (e.g., encryption, compression, watermarking, integrity check (e.g., CRC, etc.)). Thecontrol information160 indicates which steps of the DS error encoding are active for thedata92 and, for active steps, indicates the parameters for the step. For example, thecontrol information160 indicates that the error encoding is active and includes error encoding parameters (e.g., pillar width, decode threshold, write threshold, read threshold, type of error encoding, etc.).

Thegrouping selector module114 groups the encodedslices218 of the data segments into pillars ofslices216. The number of pillars corresponds to the pillar width of the DS error encoding parameters. In this example, the distributedtask control module118 facilitates the storage request.

FIG. 22 is a schematic block diagram of an example of a dispersed storage (DS)error encoding module112 for the example ofFIG. 21. The DSerror encoding module112 includes asegment processing module142, a segmentsecurity processing module144, anerror encoding module146, aslicing module148, and a per slicesecurity processing module150. Each of these modules is coupled to acontrol module116 to receivecontrol information160 therefrom.

In an example of operation, thesegment processing module142 receivesdata92 and receives segmenting information ascontrol information160 from thecontrol module116. The segmenting information indicates how the segment processing module is to segment the data. For example, the segmenting information indicates the size of each data segment. Thesegment processing module142 segments thedata92 intodata segments152 in accordance with the segmenting information.

The segmentsecurity processing module144, when enabled by thecontrol module116, secures thedata segments152 based on segment security information received ascontrol information160 from thecontrol module116. The segment security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the segmentsecurity processing module144 is enabled, it compresses adata segment152, encrypts the compressed data segment, and generates a CRC value for the encrypted data segment to produce a secure data segment. When the segmentsecurity processing module144 is not enabled, it passes thedata segments152 to theerror encoding module146 or is bypassed such that thedata segments152 are provided to theerror encoding module146.

Theerror encoding module146 encodes the secure data segments in accordance with error correction encoding parameters received ascontrol information160 from thecontrol module116. The error correction encoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction encoding parameters identify a specific error correction encoding scheme, specifies a pillar width of five, and specifies a decode threshold of three. From these parameters, theerror encoding module146 encodes a data segment to produce an encoded data segment.

Theslicing module148 slices the encoded data segment in accordance with a pillar width of the error correction encoding parameters. For example, if the pillar width is five, the slicing module slices an encoded data segment into a set of five encoded data slices. As such, for a plurality of data segments, theslicing module148 outputs a plurality of sets of encoded data slices as shown within encoding and slicingfunction222 as described.

The per slicesecurity processing module150, when enabled by thecontrol module116, secures each encoded data slice based on slice security information received ascontrol information160 from thecontrol module116. The slice security information includes data compression, encryption, watermarking, integrity check (e.g., CRC, etc.), and/or any other type of digital security. For example, when the per slicesecurity processing module150 is enabled, it may compress an encoded data slice, encrypt the compressed encoded data slice, and generate a CRC value for the encrypted encoded data slice to produce a secure encoded data slice tweaking. When the per slicesecurity processing module150 is not enabled, it passes the encoded data slices or is bypassed such that the encoded data slices218 are the output of the DSerror encoding module112.

FIG. 23 is a diagram of an example of convertingdata92 into pillar slice groups utilizing encoding, slicing andpillar grouping function224 for storage in memory of a distributed storage and task network (DSTN) module. As previously discussed thedata92 is encoded and sliced into a plurality of sets of encoded data slices; one set per data segment. The grouping selector module organizes the sets of encoded data slices into pillars of data slices. In this example, the DS error encoding parameters include a pillar width of 5 and a decode threshold of 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selector module takes the first encoded data slice of each of the sets and forms a first pillar, which may be sent to the first DST execution unit. Similarly, the grouping selector module creates the second pillar from the second slices of the sets; the third pillar from the third slices of the sets; the fourth pillar from the fourth slices of the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributed storage and/or task (DST) execution unit that includes aninterface169, acontroller86,memory88, one or more distributed task (DT)execution modules90, and aDST client module34. Acomputing core26 may be utilized to implement the one or moreDT execution modules90 and theDST client module34. Thememory88 is of sufficient size to store a significant number of encoded data slices (e.g., thousands of slices to hundreds-of-millions of slices) and may include one or more hard drives and/or one or more solid-state memory devices (e.g., flash memory, DRAM, etc.).

In an example of storing a pillar ofslices216, the DST execution unit receives, viainterface169, a pillar of slices216 (e.g.,pillar #1 slices). Thememory88 stores the encoded data slices216 of the pillar of slices in accordance withmemory control information174 it receives from thecontroller86. The controller86 (e.g., a processing module, a CPU, etc.) generates thememory control information174 based on distributed storage information (e.g., user information (e.g., user ID, distributed storage permissions, data access permission, etc.), vault information (e.g., virtual memory assigned to user, user group, etc.), etc.). Similarly, when retrieving slices, the DST execution unit receives, viainterface169, a slice retrieval request. Thememory88 retrieves the slice in accordance withmemory control information174 it receives from thecontroller86. Thememory88 outputs theslice100, via theinterface169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of an inbound distributed storage and/or task (DST)processing section82 for retrieving dispersed error encodeddata92. The inboundDST processing section82 includes ade-grouping module180, a dispersed storage (DS)error decoding module182, adata de-partitioning module184, acontrol module186, and a distributedtask control module188. Note that thecontrol module186 and/or the distributedtask control module188 may be separate modules from corresponding ones of an outbound DST processing section or may be the same modules.

In an example of operation, the inboundDST processing section82 is retrieving storeddata92 from the DST execution units (i.e., the DSTN module). In this example, the DST execution units output encoded data slices corresponding to data retrieval requests from the distributedtask control module188. Thede-grouping module180 receives pillars ofslices100 and de-groups them in accordance withcontrol information190 from thecontrol module186 to produce sets of encoded data slices218. The DSerror decoding module182 decodes, in accordance with the DS error encoding parameters received ascontrol information190 from thecontrol module186, each set of encoded data slices218 to produce data segments, which are aggregated into retrieveddata92. The datade-partitioning module184 is by-passed in this operational mode via abypass signal226 ofcontrol information190 from thecontrol module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersed storage (DS)error decoding module182 of an inbound distributed storage and task (DST) processing section. The DSerror decoding module182 includes an inverse per slicesecurity processing module202, ade-slicing module204, anerror decoding module206, an inversesegment security module208, and ade-segmenting processing module210. The dispersederror decoding module182 is operable to de-slice and decode encoded slices perdata segment218 utilizing a de-slicing anddecoding function228 to produce a plurality of data segments that are de-segmented utilizing ade-segment function230 to recoverdata92.

In an example of operation, the inverse per slicesecurity processing module202, when enabled by thecontrol module186 viacontrol information190, unsecures each encodeddata slice218 based on slice de-security information (e.g., the compliment of the slice security information discussed with reference toFIG. 6) received ascontrol information190 from thecontrol module186. The slice de-security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC verification, etc.), and/or any other type of digital security. For example, when the inverse per slicesecurity processing module202 is enabled, it verifies integrity information (e.g., a CRC value) of each encodeddata slice218, it decrypts each verified encoded data slice, and decompresses each decrypted encoded data slice to produce slice encoded data. When the inverse per slicesecurity processing module202 is not enabled, it passes the encoded data slices218 as the sliced encoded data or is bypassed such that the retrieved encoded data slices218 are provided as the sliced encoded data.

Thede-slicing module204 de-slices the sliced encoded data into encoded data segments in accordance with a pillar width of the error correction encoding parameters received ascontrol information190 from acontrol module186. For example, if the pillar width is five, the de-slicing module de-slices a set of five encoded data slices into an encoded data segment. Alternatively, the encoded data segment may include just three encoded data slices (e.g., when the decode threshold is 3).

Theerror decoding module206 decodes the encoded data segments in accordance with error correction decoding parameters received ascontrol information190 from thecontrol module186 to produce secure data segments. The error correction decoding parameters include identifying an error correction encoding scheme (e.g., forward error correction algorithm, a Reed-Solomon based algorithm, an information dispersal algorithm, etc.), a pillar width, a decode threshold, a read threshold, a write threshold, etc. For example, the error correction decoding parameters identify a specific error correction encoding scheme, specify a pillar width of five, and specify a decode threshold of three.

The inverse segmentsecurity processing module208, when enabled by thecontrol module186, unsecures the secured data segments based on segment security information received ascontrol information190 from thecontrol module186. The segment security information includes data decompression, decryption, de-watermarking, integrity check (e.g., CRC, etc.) verification, and/or any other type of digital security. For example, when the inverse segment security processing module is enabled, it verifies integrity information (e.g., a CRC value) of each secure data segment, it decrypts each verified secured data segment, and decompresses each decrypted secure data segment to produce adata segment152. When the inverse segmentsecurity processing module208 is not enabled, it passes the decodeddata segment152 as the data segment or is bypassed. Thede-segmenting processing module210 aggregates thedata segments152 into thedata92 in accordance withcontrol information190 from thecontrol module186.

FIG. 27 is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module that includes a plurality of distributed storage and task (DST) execution units (#1 through #n, where, for example, n is an integer greater than or equal to three). Each of the DST execution units includes aDST client module34, acontroller86, one or more DT (distributed task)execution modules90, andmemory88.

In this example, the DSTN module stores, in the memory of the DST execution units, a plurality of DS (dispersed storage) encoded data (e.g.,1 through n, where n is an integer greater than or equal to two) and stores a plurality of DS encoded task codes (e.g.,1 through k, where k is an integer greater than or equal to two). The DS encoded data may be encoded in accordance with one or more examples described with reference toFIGS. 3-19 (e.g., organized in slice groupings) or encoded in accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encoded into the DS encoded data may be of any size and/or of any content. For example, the data may be one or more digital books, a copy of a company's emails, a large-scale Internet search, a video security file, one or more entertainment video files (e.g., television programs, movies, etc.), data files, and/or any other large amount of data (e.g., greater than a few Terabytes).

The tasks that are encoded into the DS encoded task code may be a simple function (e.g., a mathematical function, a logic function, an identify function, a find function, a search engine function, a replace function, etc.), a complex function (e.g., compression, human and/or computer language translation, text-to-voice conversion, voice-to-text conversion, etc.), multiple simple and/or complex functions, one or more algorithms, one or more applications, etc. The tasks may be encoded into the DS encoded task code in accordance with one or more examples described with reference toFIGS. 3-19 (e.g., organized in slice groupings) or encoded in accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of a DST processing unit issues a DST request to the DSTN module. The DST request may include a request to retrieve stored data, or a portion thereof, may include a request to store data that is included with the DST request, may include a request to perform one or more tasks on stored data, may include a request to perform one or more tasks on data included with the DST request, etc. In the cases where the DST request includes a request to store data or to retrieve data, the client module and/or the DSTN module processes the request as previously discussed with reference to one or more ofFIGS. 3-19 (e.g., slice groupings) and/or20-26 (e.g., pillar groupings). In the case where the DST request includes a request to perform one or more tasks on data included with the DST request, the DST client module and/or the DSTN module process the DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one or more tasks on stored data, the DST client module and/or the DSTN module processes the DST request as will be described with reference to one or more ofFIGS. 28-39. In general, the DST client module identifies data and one or more tasks for the DSTN module to execute upon the identified data. The DST request may be for a one-time execution of the task or for an on-going execution of the task. As an example of the latter, as a company generates daily emails, the DST request may be to daily search new emails for inappropriate content and, if found, record the content, the email sender(s), the email recipient(s), email routing information, notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributed computing system performing tasks on stored data. In this example, two distributed storage and task (DST) client modules1-2 are shown: the first may be associated with a user device and the second may be associated with a DST processing unit or a high priority user device (e.g., high priority clearance user, system administrator, etc.). Each DST client module includes a list of storeddata234 and a list oftasks codes236. The list of storeddata234 includes one or more entries of data identifying information, where each entry identifies data stored in theDSTN module22. The data identifying information (e.g., data ID) includes one or more of a data file name, a data file directory listing, DSTN addressing information of the data, a data object identifier, etc. The list oftasks236 includes one or more entries of task code identifying information, when each entry identifies task codes stored in theDSTN module22. The task code identifying information (e.g., task ID) includes one or more of a task file name, a task file directory listing, DSTN addressing information of the task, another type of identifier to identify the task, etc.

As shown, the list ofdata234 and the list oftasks236 are each smaller in number of entries for the first DST client module than the corresponding lists of the second DST client module. This may occur because the user device associated with the first DST client module has fewer privileges in the distributed computing system than the device associated with the second DST client module. Alternatively, this may occur because the user device associated with the first DST client module serves fewer users than the device associated with the second DST client module and is restricted by the distributed computing system accordingly. As yet another alternative, this may occur through no restraints by the distributed computing system, it just occurred because the operator of the user device associated with the first DST client module has selected fewer data and/or fewer tasks than the operator of the device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries238 and one ormore tasks240 from its respective lists (e.g., selected data ID and selected task ID). The first DST client module sends its selections to atask distribution module232. Thetask distribution module232 may be within a stand-alone device of the distributed computing system, may be within the user device that contains the first DST client module, or may be within theDSTN module22.

Regardless of the task distribution module's location, it generatesDST allocation information242 from the selectedtask ID240 and the selecteddata ID238. TheDST allocation information242 includes data partitioning information, task execution information, and/or intermediate result information. Thetask distribution module232 sends theDST allocation information242 to theDSTN module22. Note that one or more examples of the DST allocation information will be discussed with reference to one or more ofFIGS. 29-39.

TheDSTN module22 interprets theDST allocation information242 to identify the stored DS encoded data (e.g., DS error encoded data2) and to identify the stored DS error encoded task code (e.g., DS error encoded task code1). In addition, theDSTN module22 interprets theDST allocation information242 to determine how the data is to be partitioned and how the task is to be partitioned. TheDSTN module22 also determines whether the selected DS error encodeddata238 needs to be converted from pillar grouping to slice grouping. If so, theDSTN module22 converts the selected DS error encoded data into slice groupings and stores the slice grouping DS error encoded data by overwriting the pillar grouping DS error encoded data or by storing it in a different location in the memory of the DSTN module22 (i.e., does not overwrite the pillar grouping DS encoded data).

TheDSTN module22 partitions the data and the task as indicated in theDST allocation information242 and sends the portions to selected DST execution units of theDSTN module22. Each of the selected DST execution units performs its partial task(s) on its slice groupings to produce partial results. TheDSTN module22 collects the partial results from the selected DST execution units and provides them, asresult information244, to the task distribution module. Theresult information244 may be the collected partial results, one or more final results as produced by theDSTN module22 from processing the partial results in accordance with theDST allocation information242, or one or more intermediate results as produced by theDSTN module22 from processing the partial results in accordance with theDST allocation information242.

Thetask distribution module232 receives theresult information244 and provides one or morefinal results104 therefrom to the first DST client module. The final result(s)104 may beresult information244 or a result(s) of the task distribution module's processing of theresult information244.

In concurrence with processing the selected task of the first DST client module, the distributed computing system may process the selected task(s) of the second DST client module on the selected data(s) of the second DST client module. Alternatively, the distributed computing system may process the second DST client module's request subsequent to, or preceding, that of the first DST client module. Regardless of the ordering and/or parallel processing of the DST client module requests, the second DST client module provides its selecteddata238 and selectedtask240 to atask distribution module232. If thetask distribution module232 is a separate device of the distributed computing system or within the DSTN module, thetask distribution modules232 coupled to the first and second DST client modules may be the same module. Thetask distribution module232 processes the request of the second DST client module in a similar manner as it processed the request of the first DST client module.

FIG. 29 is a schematic block diagram of an embodiment of atask distribution module232 facilitating the example ofFIG. 28. Thetask distribution module232 includes a plurality of tables it uses to generate distributed storage and task (DST)allocation information242 for selected data and selected tasks received from a DST client module. The tables includedata storage information248,task storage information250, distributed task (DT)execution module information252, and task

sub-task mapping information246.

The data storage information table248 includes a data identification (ID)field260, adata size field262, an addressinginformation field264, distributed storage (DS)information266, and may further include other information regarding the data, how it is stored, and/or how it can be processed. For example, DS encodeddata #1 has a data ID of 1, a data size of AA (e.g., a byte size of a few Terabytes or more), addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1; and SLC_1. In this example, the addressing information may be a virtual address corresponding to the virtual address of the first storage word (e.g., one or more bytes) of the data and information on how to calculate the other addresses, may be a range of virtual addresses for the storage words of the data, physical addresses of the first storage word or the storage words of the data, may be a list of slice names of the encoded data slices of the data, etc. The DS parameters may include identity of an error encoding scheme, decode threshold/pillar width (e.g., 3/5 for the first data entry), segment security information (e.g., SEG_1), per slice security information (e.g., SLC_1), and/or any other information regarding how the data was encoded into data slices.

The task storage information table250 includes a task identification (ID)field268, atask size field270, an addressinginformation field272, distributed storage (DS)information274, and may further include other information regarding the task, how it is stored, and/or how it can be used to process data. For example, DS encodedtask #2 has a task ID of 2, a task size of XY, addressing information of Addr_2_XY, and DS parameters of 3/5; SEG_2; and SLC_2. In this example, the addressing information may be a virtual address corresponding to the virtual address of the first storage word (e.g., one or more bytes) of the task and information on how to calculate the other addresses, may be a range of virtual addresses for the storage words of the task, physical addresses of the first storage word or the storage words of the task, may be a list of slices names of the encoded slices of the task code, etc. The DS parameters may include identity of an error encoding scheme, decode threshold/pillar width (e.g., 3/5 for the first data entry), segment security information (e.g., SEG_2), per slice security information (e.g., SLC_2), and/or any other information regarding how the task was encoded into encoded task slices. Note that the segment and/or the per-slice security information include a type of encryption (if enabled), a type of compression (if enabled), watermarking information (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table246 includes atask field256 and asub-task field258. Thetask field256 identifies a task stored in the memory of a distributed storage and task network (DSTN) module and the correspondingsub-task fields258 indicates whether the task includes sub-tasks and, if so, how many and if any of the sub-tasks are ordered. In this example, the task

sub-task mapping information table246 includes an entry for each task stored in memory of the DSTN module (e.g.,task1 through task k). In particular, this example indicates thattask1 includes 7 sub-tasks;task2 does not include sub-tasks, and task k includes r number of sub-tasks (where r is an integer greater than or equal to two).

The DT execution module table252 includes a DST executionunit ID field276, a DT executionmodule ID field278, and a DT executionmodule capabilities field280. The DST executionunit ID field276 includes the identity of DST units in the DSTN module. The DT executionmodule ID field278 includes the identity of each DT execution unit in each DST unit. For example,DST unit1 includes three DT executions modules (e.g.,1_1,1_2, and1_3). The DTexecution capabilities field280 includes identity of the capabilities of the corresponding DT execution unit. For example, DT execution module1_1 includes capabilities X, where X includes one or more of MIPS capabilities, processing resources (e.g., quantity and capability of microprocessors, CPUs, digital signal processors, co-processor, microcontrollers, arithmetic logic circuitry, and/or any other analog and/or digital processing circuitry), availability of the processing resources, memory information (e.g., type, size, availability, etc.), and/or any information germane to executing one or more tasks.

From these tables, thetask distribution module232 generates theDST allocation information242 to indicate where the data is stored, how to partition the data, where the task is stored, how to partition the task, which DT execution units should perform which partial task on which data partitions, where and how intermediate results are to be stored, etc. If multiple tasks are being performed on the same data or different data, the task distribution module factors such information into its generation of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computing system performing tasks on stored data as atask flow318. In this example, selecteddata92 isdata2 and selected tasks aretasks1,2, and3.Task1 corresponds to analyzing translation of data from one language to another (e.g., human language or computer language);task2 corresponds to finding specific words and/or phrases in the data; andtask3 corresponds to finding specific translated words and/or phrases in translated data.

In this example,task1 includes 7 sub-tasks: task1_1—identify non-words (non-ordered); task1_2—identify unique words (non-ordered); task1_3—translate (non-ordered); task1_4 —translate back (ordered after task1_3); task1_5—compare to ID errors (ordered after task1-4); task1_6—determine non-word translation errors (ordered after task1_5 and1_1); and task1_7 —determine correct translations (ordered after1_5 and1_2). The sub-task further indicates whether they are an ordered task (i.e., are dependent on the outcome of another task) or non-order (i.e., are independent of the outcome of another task).Task2 does not include sub-tasks andtask3 includes two sub-tasks: task3_1 translate; and task3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze data for translation accuracies, translation errors, translation anomalies, occurrence of specific words or phrases in the data, and occurrence of specific words or phrases on the translated data. Graphically, thedata92 is translated306 into translateddata282; is analyzed for specific words and/orphrases300 to produce a list of specific words and/orphrases286; is analyzed for non-words302 (e.g., not in a reference dictionary) to produce a list ofnon-words290; and is analyzed forunique words316 included in the data92 (i.e., how many different words are included in the data) to produce a list ofunique words298. Each of these tasks is independent of each other and can therefore be processed in parallel if desired.

The translateddata282 is analyzed (e.g., sub-task3_2) for specific translated words and/orphrases304 to produce a list of specific translated words and/orphrases288. The translateddata282 is translated back308 (e.g., sub-task1_4) into the language of the original data to producere-translated data284. These two tasks are dependent on the translate task (e.g., task1_3) and thus must be ordered after the translation task, which may be in a pipelined ordering or a serial ordering. There-translated data284 is then compared310 with theoriginal data92 to find words and/or phrases that did not translate (one way and/or the other) properly to produce a list of incorrectly translatedwords294. As such, the comparing task (e.g., sub-task1_5)310 is ordered after thetranslation306 and re-translation tasks308 (e.g., sub-tasks1_3 and1_4).

The list of words incorrectly translated294 is compared312 to the list ofnon-words290 to identify words that were not properly translated because the words are non-words to produce a list of errors due tonon-words292. In addition, the list of words incorrectly translated294 is compared314 to the list ofunique words298 to identify unique words that were properly translated to produce a list of correctly translatedwords296. The comparison may also identify unique words that were not properly translated to produce a list of unique words that were not properly translated. Note that each list of words (e.g., specific words and/or phrases, non-words, unique words, translated words and/or phrases, etc.,) may include the word and/or phrase, how many times it is used, where in the data it is used, and/or any other information requested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributed storage and task processing network (DSTN) module storing data and task codes for the example ofFIG. 30. As shown, DS encodeddata2 is stored as encoded data slices across the memory (e.g., stored in memories88) of DST execution units1-5; the DS encoded task code1 (of task1) and DS encodedtask3 are stored as encoded task slices across the memory of DST execution units1-5; and DS encoded task code2 (of task2) is stored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the task storage information table ofFIG. 29, the respective data/task has DS parameters of 3/5 for their decode threshold/pillar width; hence spanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information242 for the example ofFIG. 30. TheDST allocation information242 includesdata partitioning information320,task execution information322, andintermediate result information324. Thedata partitioning information320 includes the data identifier (ID), the number of partitions to split the data into, address information for each data partition, and whether the DS encoded data has to be transformed from pillar grouping to slice grouping. Thetask execution information322 includes tabular information having atask identification field326, atask ordering field328, a datapartition field ID330, and a set ofDT execution modules332 to use for the distributed task processing per data partition. Theintermediate result information324 includes tabular information having aname ID field334, an ID of the DST execution unit assigned to process the correspondingintermediate result336, a scratchpad storage field338, and an intermediateresult storage field340.

Continuing with the example ofFIG. 30, where tasks1-3 are to be distributedly performed ondata2, the data partitioning information includes the ID ofdata2. In addition, the task distribution module determines whether the DS encodeddata2 is in the proper format for distributed computing (e.g., was stored as slice groupings). If not, the task distribution module indicates that the DS encodeddata2 format needs to be changed from the pillar grouping format to the slice grouping format, which will be done by the DSTN module. In addition, the task distribution module determines the number of partitions to divide the data into (e.g.,2_1 through2_z) and addressing information for each partition.

The task distribution module generates an entry in the task execution information section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e., is independent of the results of other sub-tasks), is to be performed on data partitions2_1 through2_z by DT execution modules1_1,2_1,3_1,4_1, and5_1. For instance, DT execution modules1_1,2_1,3_1,4_1, and5_1 search for non-words in data partitions2_1 through2_z to produce task1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution information as task1_1 to produce task1_2 intermediate results (R1-2, which is the list of unique words).

Task1_3 (e.g., translate) includes task execution information as being non-ordered (i.e., is independent), having DT execution modules1_1,2_1,3_1,4_1, and5_1 translate data partitions2_1 through2_4 and having DT execution modules1_2,2_2,3_2,4_2, and5_2 translate data partitions2_5 through2_z to produce task1_3 intermediate results (R1-3, which is the translated data). In this example, the data partitions are grouped, where different sets of DT execution modules perform a distributed sub-task (or task) on each data partition group, which allows for further parallel processing.

Task1_4 (e.g., translate back) is ordered after task1_3 and is to be executed on task1_3's intermediate result (e.g., R1-3_1) (e.g., the translated data). DT execution modules1_1,2_1,3_1,4_1, and5_1 are allocated to translate back task1_3 intermediate result partitions R1-3_1 through R1-3_4 and DT execution modules1_2,2_2,6_1,7_1, and7_2 are allocated to translate back task1_3 intermediate result partitions R1-3_5 through R1-3_z to produce task1-4 intermediate results (R1-4, which is the translated back data).

Task1_5 (e.g., compare data and translated data to identify translation errors) is ordered after task1_4 and is to be executed on task1_4's intermediate results (R4-1) and on the data. DT execution modules1_1,2_1,3_1,4_1, and5_1 are allocated to compare the data partitions (2_1 through2_z) with partitions of task1-4 intermediate results partitions R1-4_1 through R1-4_z to produce task1_5 intermediate results (R1-5, which is the list words translated incorrectly).

Task1_6 (e.g., determine non-word translation errors) is ordered after tasks1_1 and1_5 and is to be executed on tasks1_1's and1_5's intermediate results (R1-1 and R1-5). DT execution modules1_1,2_1,3_1,4_1, and5_1 are allocated to compare the partitions of task1_1 intermediate results (R1-1_1 through R1-1_z) with partitions of task1-5 intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors due to non-words).

Task1_7 (e.g., determine words correctly translated) is ordered after tasks1_2 and1_5 and is to be executed on tasks1_2's and1_5's intermediate results (R1-1 and R1-5). DT execution modules1_2,2_2,3_2,4_2, and5_2 are allocated to compare the partitions of task1_2 intermediate results (R1-2_1 through R1-2_z) with partitions of task1-5 intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctly translated words).

Task2 (e.g., find specific words and/or phrases) has no task ordering (i.e., is independent of the results of other sub-tasks), is to be performed on data partitions2_1 through2_z by DT execution modules3_1,4_1,5_1,6_1, and7_1. For instance, DT execution modules3_1,4_1,5_1,6_1, and7_1 search for specific words and/or phrases in data partitions2_1 through2_z to producetask2 intermediate results (R2, which is a list of specific words and/or phrases).

Task3_2 (e.g., find specific translated words and/or phrases) is ordered after task1_3 (e.g., translate) is to be performed on partitions R1-3_1 through R1-3_z by DT execution modules1_2,2_2,3_2,4_2, and5_2. For instance, DT execution modules1_2,2_2,3_2,4_2, and5_2 search for specific translated words and/or phrases in the partitions of the translated data (R1-3_1 through R1-3_z) to produce task3_2 intermediate results (R3-2, which is a list of specific translated words and/or phrases).

For each task, the intermediate result information indicates which DST unit is responsible for overseeing execution of the task and, if needed, processing the partial results generated by the set of allocated DT execution units. In addition, the intermediate result information indicates a scratch pad memory for the task and where the corresponding intermediate results are to be stored. For example, for intermediate result R1-1 (the intermediate result of task1_1),DST unit1 is responsible for overseeing execution of the task1_1 and coordinates storage of the intermediate result as encoded intermediate result slices stored in memory of DST execution units1-5. In general, the scratch pad is for storing non-DS encoded intermediate results and the intermediate result storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage and task network (DSTN) module performing the example ofFIG. 30. InFIG. 33, the DSTN module accesses thedata92 and partitions it into a plurality of partitions1-z in accordance with distributed storage and task network (DST) allocation information. For each data partition, the DSTN identifies a set of its DT (distributed task)execution modules90 to perform the task (e.g., identify non-words (i.e., not in a reference dictionary) within the data partition) in accordance with the DST allocation information. From data partition to data partition, the set ofDT execution modules90 may be the same, different, or a combination thereof (e.g., some data partitions use the same set while other data partitions use different sets).

For the first data partition, the first set of DT execution modules (e.g.,1_1,2_1,3_1,4_1, and5_1 per the DST allocation information ofFIG. 32) executes task1_1 to produce a firstpartial result102 of non-words found in the first data partition. The second set of DT execution modules (e.g.,1_1,2_1,3_1,4_1, and5_1 per the DST allocation information ofFIG. 32) executes task1_1 to produce a secondpartial result102 of non-words found in the second data partition. The sets of DT execution modules (as per the DST allocation information) perform task1_1 on the data partitions until the “z” set of DT execution modules performs task1_1 on the “zth” data partition to produce a “zth”partial result102 of non-words found in the “zth” data partition.

As indicated in the DST allocation information ofFIG. 32,DST execution unit1 is assigned to process the first through “zth” partial results to produce the first intermediate result (R1-1), which is a list of non-words found in the data. For instance, each set ofDT execution modules90 stores its respective partial result in the scratchpad memory of DST execution unit1 (which is identified in the DST allocation or may be determined by DST execution unit1). A processing module ofDST execution1 is engaged to aggregate the first through “zth” partial results to produce the first intermediate result (e.g., R1_1). The processing module stores the first intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit1.

DST execution unit1 engages its DST client module to slice grouping based DS error encode the first intermediate result (e.g., the list of non-words). To begin the encoding, the DST client module determines whether the list of non-words is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the first intermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1 through R1-1_m). If the first intermediate result is not of sufficient size to partition, it is not partitioned.

For each partition of the first intermediate result, or for the first intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units1-5).

InFIG. 34, the DSTN module is performing task1_2 (e.g., find unique words) on thedata92. To begin, the DSTN module accesses thedata92 and partitions it into a plurality of partitions1-z in accordance with the DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTN identifies a set of its DT execution modules to perform task1_2 in accordance with the DST allocation information. From data partition to data partition, the set of DT execution modules may be the same, different, or a combination thereof. For the data partitions, the allocated set of DT execution modules executes task1_2 to produce a partial results (e.g., 1^stthrough “zth”) of unique words found in the data partitions.

As indicated in the DST allocation information ofFIG. 32,DST execution unit1 is assigned to process the first through “zth”partial results102 of task1_2 to produce the second intermediate result (R1-2), which is a list of unique words found in thedata92. The processing module ofDST execution1 is engaged to aggregate the first through “zth” partial results of unique words to produce the second intermediate result. The processing module stores the second intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit1.

DST execution unit1 engages its DST client module to slice grouping based DS error encode the second intermediate result (e.g., the list of non-words). To begin the encoding, the DST client module determines whether the list of unique words is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions the second intermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1 through R1-2_m). If the second intermediate result is not of sufficient size to partition, it is not partitioned.

For each partition of the second intermediate result, or for the second intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units1-5).

InFIG. 35, the DSTN module is performing task1_3 (e.g., translate) on thedata92. To begin, the DSTN module accesses thedata92 and partitions it into a plurality of partitions1-z in accordance with the DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTN identifies a set of its DT execution modules to perform task1_3 in accordance with the DST allocation information (e.g., DT execution modules1_1,2_1,3_1,4_1, and5_1 translate data partitions2_1 through2_4 and DT execution modules1_2,2_2,3_2,4_2, and5_2 translate data partitions2_5 through2_z). For the data partitions, the allocated set ofDT execution modules90 executes task1_3 to produce partial results102 (e.g., 1^stthrough “zth”) of translated data.

As indicated in the DST allocation information ofFIG. 32,DST execution unit2 is assigned to process the first through “zth” partial results of task1_3 to produce the third intermediate result (R1-3), which is translated data. The processing module ofDST execution2 is engaged to aggregate the first through “zth” partial results of translated data to produce the third intermediate result. The processing module stores the third intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit2.

DST execution unit2 engages its DST client module to slice grouping based DS error encode the third intermediate result (e.g., translated data). To begin the encoding, the DST client module partitions the third intermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1 through R1-3_y). For each partition of the third intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units2-6 per the DST allocation information).

As is further shown inFIG. 35, the DSTN module is performing task1_4 (e.g., retranslate) on the translated data of the third intermediate result. To begin, the DSTN module accesses the translated data (from the scratchpad memory or from the intermediate result memory and decodes it) and partitions it into a plurality of partitions in accordance with the DST allocation information. For each partition of the third intermediate result, the DSTN identifies a set of itsDT execution modules90 to perform task1_4 in accordance with the DST allocation information (e.g., DT execution modules1_1,2_1,3_1,4_1, and5_1 are allocated to translate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2,2_2,6_1,7_1, and7_2 are allocated to translate back partitions R1-3_5 through R1-3_z). For the partitions, the allocated set of DT execution modules executes task1_4 to produce partial results102 (e.g., 1^stthrough “zth”) of re-translated data.

As indicated in the DST allocation information ofFIG. 32,DST execution unit3 is assigned to process the first through “zth” partial results of task1_4 to produce the fourth intermediate result (R1-4), which is retranslated data. The processing module ofDST execution3 is engaged to aggregate the first through “zth” partial results of retranslated data to produce the fourth intermediate result. The processing module stores the fourth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit3.

DST execution unit3 engages its DST client module to slice grouping based DS error encode the fourth intermediate result (e.g., retranslated data). To begin the encoding, the DST client module partitions the fourth intermediate result (R1-4) into a plurality of partitions (e.g., R1-4_—1 through R1-4_z). For each partition of the fourth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units3-7 per the DST allocation information).

InFIG. 36, a distributed storage and task network (DSTN) module is performing task1_5 (e.g., compare) ondata92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses thedata92 and partitions it into a plurality of partitions in accordance with the DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. The DSTN module also accesses the retranslated data from the scratchpad memory, or from the intermediate result memory and decodes it, and partitions it into a plurality of partitions in accordance with the DST allocation information. The number of partitions of the retranslated data corresponds to the number of partitions of the data.

For each pair of partitions (e.g.,data partition1 and retranslated data partition1), the DSTN identifies a set of itsDT execution modules90 to perform task1_5 in accordance with the DST allocation information (e.g., DT execution modules1_1,2_1,3_1,4_1, and5_1). For each pair of partitions, the allocated set of DT execution modules executes task1_5 to produce partial results102 (e.g., 1^stthrough “zth”) of a list of incorrectly translated words and/or phrases.

As indicated in the DST allocation information ofFIG. 32,DST execution unit1 is assigned to process the first through “zth” partial results of task1_5 to produce the fifth intermediate result (R1-5), which is the list of incorrectly translated words and/or phrases. In particular, the processing module ofDST execution1 is engaged to aggregate the first through “zth” partial results of the list of incorrectly translated words and/or phrases to produce the fifth intermediate result. The processing module stores the fifth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit1.

DST execution unit1 engages its DST client module to slice grouping based DS error encode the fifth intermediate result. To begin the encoding, the DST client module partitions the fifth intermediate result (R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). For each partition of the fifth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units1-5 per the DST allocation information).

As is further shown inFIG. 36, the DSTN module is performing task1_6 (e.g., translation errors due to non-words) on the list of incorrectly translated words and/or phrases (e.g., the fifth intermediate result R1-5) and the list of non-words (e.g., the first intermediate result R1-1). To begin, the DSTN module accesses the lists and partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partition R1-5_1), the DSTN identifies a set of itsDT execution modules90 to perform task1_6 in accordance with the DST allocation information (e.g., DT execution modules1_1,2_1,3_1,4_1, and5_1). For each pair of partitions, the allocated set of DT execution modules executes task1_6 to produce partial results102 (e.g., 1^stthrough “zth”) of a list of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information ofFIG. 32,DST execution unit2 is assigned to process the first through “zth” partial results of task1_6 to produce the sixth intermediate result (R1-6), which is the list of incorrectly translated words and/or phrases due to non-words. In particular, the processing module ofDST execution2 is engaged to aggregate the first through “zth” partial results of the list of incorrectly translated words and/or phrases due to non-words to produce the sixth intermediate result. The processing module stores the sixth intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit2.

DST execution unit2 engages its DST client module to slice grouping based DS error encode the sixth intermediate result. To begin the encoding, the DST client module partitions the sixth intermediate result (R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z). For each partition of the sixth intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units2-6 per the DST allocation information).

As is still further shown inFIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list of incorrectly translated words and/or phrases (e.g., the fifth intermediate result R1-5) and the list of unique words (e.g., the second intermediate result R1-2). To begin, the DSTN module accesses the lists and partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partition R1-5_1), the DSTN identifies a set of itsDT execution modules90 to perform task1_7 in accordance with the DST allocation information (e.g., DT execution modules1_2,2_2,3_2,4_2, and5_2). For each pair of partitions, the allocated set of DT execution modules executes task1_7 to produce partial results102 (e.g., 1^stthrough “zth”) of a list of correctly translated words and/or phrases.

As indicated in the DST allocation information ofFIG. 32,DST execution unit3 is assigned to process the first through “zth” partial results of task1_7 to produce the seventh intermediate result (R1-7), which is the list of correctly translated words and/or phrases. In particular, the processing module ofDST execution3 is engaged to aggregate the first through “zth” partial results of the list of correctly translated words and/or phrases to produce the seventh intermediate result. The processing module stores the seventh intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit3.

DST execution unit3 engages its DST client module to slice grouping based DS error encode the seventh intermediate result. To begin the encoding, the DST client module partitions the seventh intermediate result (R1-7) into a plurality of partitions (e.g., R1-7_1 through R1-7_z). For each partition of the seventh intermediate result, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units3-7 per the DST allocation information).

InFIG. 37, the distributed storage and task network (DSTN) module is performing task2 (e.g., find specific words and/or phrases) on thedata92. To begin, the DSTN module accesses the data and partitions it into a plurality of partitions1-z in accordance with the DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTN identifies a set of itsDT execution modules90 to performtask2 in accordance with the DST allocation information. From data partition to data partition, the set of DT execution modules may be the same, different, or a combination thereof. For the data partitions, the allocated set of DT execution modules executestask2 to produce partial results102 (e.g., 1^stthrough “zth”) of specific words and/or phrases found in the data partitions.

As indicated in the DST allocation information ofFIG. 32,DST execution unit7 is assigned to process the first through “zth” partial results oftask2 to producetask2 intermediate result (R2), which is a list of specific words and/or phrases found in the data. The processing module ofDST execution7 is engaged to aggregate the first through “zth” partial results of specific words and/or phrases to produce thetask2 intermediate result. The processing module stores thetask2 intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit7.

DST execution unit7 engages its DST client module to slice grouping based DS error encode thetask2 intermediate result. To begin the encoding, the DST client module determines whether the list of specific words and/or phrases is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions thetask2 intermediate result (R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask2 intermediate result is not of sufficient size to partition, it is not partitioned.

For each partition of thetask2 intermediate result, or for thetask2 intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units1-4, and7).

InFIG. 38, the distributed storage and task network (DSTN) module is performing task 3 (e.g., find specific translated words and/or phrases) on the translated data (R1-3). To begin, the DSTN module accesses the translated data (from the scratchpad memory or from the intermediate result memory and decodes it) and partitions it into a plurality of partitions in accordance with the DST allocation information. For each partition, the DSTN identifies a set of its DT execution modules to performtask3 in accordance with the DST allocation information. From partition to partition, the set of DT execution modules may be the same, different, or a combination thereof. For the partitions, the allocated set ofDT execution modules90 executestask3 to produce partial results102 (e.g., 1^stthrough “zth”) of specific translated words and/or phrases found in the data partitions.

As indicated in the DST allocation information ofFIG. 32,DST execution unit5 is assigned to process the first through “zth” partial results oftask3 to producetask3 intermediate result (R3), which is a list of specific translated words and/or phrases found in the translated data. In particular, the processing module ofDST execution5 is engaged to aggregate the first through “zth” partial results of specific translated words and/or phrases to produce thetask3 intermediate result. The processing module stores thetask3 intermediate result as non-DS error encoded data in the scratchpad memory or in another section of memory ofDST execution unit7.

DST execution unit5 engages its DST client module to slice grouping based DS error encode thetask3 intermediate result. To begin the encoding, the DST client module determines whether the list of specific translated words and/or phrases is of a sufficient size to partition (e.g., greater than a Terabyte). If yes, it partitions thetask3 intermediate result (R3) into a plurality of partitions (e.g., R3_1 through R3_m). If thetask3 intermediate result is not of sufficient size to partition, it is not partitioned.

For each partition of thetask3 intermediate result, or for thetask3 intermediate results, the DST client module uses the DS error encoding parameters of the data (e.g., DS parameters ofdata2, which includes 3/5 decode threshold/pillar width ratio) to produce slice groupings. The slice groupings are stored in the intermediate result memory (e.g., allocated memory in the memories of DST execution units1-4,5, and7).

FIG. 39 is a diagram of an example of combining result information intofinal results104 for the example ofFIG. 30. In this example, the result information includes the list of specific words and/or phrases found in the data (task2 intermediate result), the list of specific translated words and/or phrases found in the data (task3 intermediate result), the list of non-words found in the data (task1 first intermediate result R1-1), the list of unique words found in the data (task1 second intermediate result R1-2), the list of translation errors due to non-words (task1 sixth intermediate result R1-6), and the list of correctly translated words and/or phrases (task1 seventh intermediate result R1-7). The task distribution module provides the result information to the requesting DST client module as theresults104.

FIGS. 40A-40D are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of storing data in DSN memory. The DSN includes the distributed storage and task (DST)client module34 ofFIG. 1, thenetwork24 ofFIG. 1, and the distributed storage and task network (DSTN)module22 ofFIG. 1. Hereafter, theDSTN module22 may be referred to interchangeably as the DSN memory. TheDSTN module22 includes one or more storage generations, where each storage generation is associated with a vault of the DSN. A vault includes virtual storage of the DSN and may be associated with one or more users of the DSN. Incremental storage generations may be added over time to provide incremental storage capacity as a total amount of data stored associated with the vault grows. For example, theDSTN module22 includes storage generations1-3 during a first timeframe (e.g., as illustrated inFIGS. 40A-B) and includes storage generations1-5 during a second timeframe (e.g., as illustrated inFIGS. 40C-D). Each storage generation includes a set of DST execution (EX) units1-n. Each DST execution unit may be implemented utilizing theDST execution unit36 ofFIG. 1. Hereafter, the DST execution unit may be referred to interchangeably as a storage unit of a set of storage units associated with each storage generation.

TheDST client module34 includes theoutbound DST processing80 ofFIG. 3, theinbound DST processing82 ofFIG. 3, and aslice name module350. Theslice name module350 may be implemented utilizing theprocessing module84 ofFIG. 3. TheDST client module34 further includes a dispersed storage (DS)module351. TheDS module351 may be implemented utilizing a plurality of processing modules. For instance, the plurality of processing modules may include theprocessing module84 ofFIG. 3. As a specific example, the plurality of processing module includes a first module, a second module, a third module, a fourth module, a fifth module, and a sixth module. The first through sixth modules may be utilized to implement theoutbound DST processing80, theinbound DST processing82, and theslice name module350. The DSN functions to accessdata352 in theDSTN module22 without utilizing a directory. The accessing of thedata352 includes storing of thedata352 and retrieving stored data to reproduce thedata352.

FIG. 40A illustrates initial steps of an example of the storing of thedata352, where theoutbound DST processing80 receives thedata352 for storage, where the data has a data name. The data name includes file system information. The file system information includes one or more of a user identifier (ID), a vault identifier, and a file system path name for the data. Having received thedata352, theoutbound DST processing80 dispersed storage error encodes thedata352 to produce a plurality of sets of encoded data slices.

Having produced the plurality of sets of encoded data slices, theoutbound DST processing80 generates a plurality of sets of DSN data addresses based on a data object number associated with the data and data storage information. Each set of the plurality of sets of DSN data addresses includes a set of DSN addresses, where the set of DSN addresses includes a set of slice names. Each slice name includes one or more of a slice index corresponding to a particular slice of the set of encoded data slices, a vault ID corresponding to an associated vault, a generation number corresponding to one of the storage generations, the data object number, and a segment number corresponding to the set of encoded data slices. As a specific example, theoutbound DST processing80 utilizes a pseudo random number generator to produce the data object number, performs a system registry lookup to retrieve the vault ID corresponding to a requesting entity, and selects a storage generation of the storage generations to produce the generation number.

The selecting of the storage generation for storing of thedata352 includes at least one of a random selection, selecting a most recently activated storage generation, selecting a storage generation associated with a highest storage availability level, selecting a storage generation based on interpreting a data storage request, selecting a storage generation based on interpreting a system registry entry, and selecting a storage generation associated with a storage availability level that is greater than a storage availability threshold level. For instance, theoutbound DST processing80 selects a most recently activatedstorage generation3 as the selected storage generation to producegeneration number3.

The data storage information includes dispersed storage error encoding parameters. The dispersed storage error encoding parameters includes one or more of data segmenting information regarding segmenting thedata352 into a plurality of data segments, a total number of encoded data slices per set of encoded data slices, a decode threshold number of encoded data slices per set of encoded data slices, a read threshold number of encoded data slices per set of encoded data slices, and a write threshold number of encoded data slices per the set of encoded data slices. Theoutbound DST processing80 determines the data storage information. The determining includes at least one of performing a system registry lookup, receiving the dispersed storage error encoding parameters, and determining the dispersed storage error encoding parameters based on one or more of received storage requirements and an estimated DSN performance level.

Having generated the plurality of sets of DSN data addresses, theoutbound DST processing80 sends, via thenetwork24, the plurality of sets of encoded data slices to the DSTN module22 (e.g., DSN memory) for storage in accordance with the plurality of sets of DSN data addresses. As a specific example, theoutbound DST processing80 generates a set of write slice requests that includes the plurality of sets of encoded data slices and the plurality of sets of DSN data addresses, and outputs the set of write slice requests that includes the plurality of sets of encoded data slices (EDS)1-n ofgeneration3 to the set of DST execution units1-n of thestorage generation3.

FIG. 40B illustrates final steps of the example of the storing of thedata352, where theoutbound DST processing80 generates retrieval data that is based on the data object number and the data storage information. As a specific example, theoutbound DST processing80 aggregates the data object number, the vault ID and the generation number to produce the retrieval data. Having generated the retrieval data, theoutbound DST processing80 dispersed storage error encodes the retrieval data to produce a set of encoded retrieval data slices.

With the set of encoded retrieval data slices produced, theslice name module350 generates a set of DSN retrieval data addresses356 based on thedata name354 and on retrieval data storage information. The set of DSN retrieval data addresses356 includes a set of slice names for the set of encoded retrieval data slices. Each slice name for a corresponding encoded retrieval data slice includes one or more of a slice index corresponding to a particular slice of the set of encoded retrieval data slices, the vault ID, a generation number for the retrieval data corresponding to at least one of the storage generations, a retrieval data object number, and a segment number corresponding to the set of encoded retrieval data slices. As a specific example,slice name module350 performs a deterministic function on thedata name354 to produce the retrieval data object number, and selects at least one storage generation of the storage generations to produce the generation number. The deterministic function includes one or more of a hashing function, a hash-based message authentication code function, a mask generating function, and a sponge function. For instance, theslice name module350 performs the mask generating function on thedata name354 to directly produce the retrieval data object number.

The selecting of the at least one storage generation for storing of the retrieval data includes at least one of a random selection, applying a deterministic function to thedata name354, selecting the most recently activated storage generation, selecting the storage generation associated with the highest storage availability level, selecting the storage generation based on interpreting the data storage request, selecting the storage generation based on interpreting the system registry entry, and selecting the storage generation associated with the storage availability level that is greater than the storage availability threshold level. For instance, theslice name module350 performs the hashing function on thedata name354 to produce an intermediate result, and takes the intermediate result modulo number of current storage generations to producegeneration number2.

The retrieval data storage information includes dispersed storage error encoding parameters for the retrieval data. The dispersed storage error encoding parameters for the retrieval data includes one or more of a total number of encoded retrieval data slices for the set of encoded retrieval data slices, a decode threshold number of encoded retrieval data slices for the set of encoded retrieval data slices, a read threshold number of encoded retrieval data slices for the set of encoded retrieval data slices, and a write threshold number of encoded retrieval data slices for the set of encoded retrieval data slices. Theoutbound DST processing80 determines the retrieval data storage information. Alternatively, theslice name module350 determines the retrieval data storage information. The determining includes at least one of performing a system registry lookup, receiving the dispersed storage error encoding parameters for the retrieval data, utilizing the dispersed storage error encoding parameters of thedata352, and determining the dispersed storage error encoding parameters for the retrieval data based on one or more of further received storage requirements and the estimated DSN performance level.

With the DSN retrieval data addresses356 produced, theoutbound DST processing80 sends, via thenetwork24, the set of encoded retrieval data slices to the DSTN module22 (e.g., DSN memory) for storage in accordance with the set of DSN retrieval data addresses356. As a specific example, theoutbound DST processing80 generates another set of write slice requests that includes the set of encoded retrieval data slices and the set of DSN retrieval data addresses356; and outputs the other set of write slice requests that includes the set of encoded retrieval data slices (ERDS)1-n ofgeneration2 to the set of DST execution units1-n of thestorage generation2.

Alternatively, or in addition to, one or more of theslice name module350 and theoutbound DST processing80 may determine to store the retrieval data in at least one other storage generation. As a specific example, theslice name module350 determines to store multiple copies of the set of encoded retrieval data slices and identifies multiple sets of storage units of the DSN memory for storing the multiple copies. The multiple sets of storage units being part of a logical storage vault within the DSN memory, where a first set of storage units of the set of storage units corresponds to a first generation of the DSN memory and a second set of storage units of the set of storage units corresponds to a second generation of the DSN memory. The determining includes one or more of detecting that a size of the retrieval data is less than a size threshold level, detecting that an available storage capacity level is greater than an available storage capacity threshold level, interpreting a system registry entry, and interpreting a request.

When determining to store multiple copies of the set of encoded retrieval data slices, theslice name module350 generates a unique set of DSN retrieval data addresses based on the data name, on the retrieval data storage information, and on a corresponding one of the multiple sets of storage units. As a specific example, theslice name module350 generates another set of DSN retrieval data addresses that includesgeneration3 when identifyingstorage generation3. With the other set of DSN retrieval data addresses, theoutbound DST processing80 sends, via thenetwork24, the set of encoded retrieval data slices to the corresponding one of the multiple sets of storage units for storage in accordance with the other set of DSN retrieval data addresses. As a specific example, theoutbound DST processing80 generates yet another set of write slice requests that includes the set of encoded retrieval data slices and the other set of DSN retrieval data addresses356; and outputs the yet another set of write slice requests that includes the set of encoded retrieval data slices (ERDS)1-n ofgeneration3 to the set of DST execution units1-n of thestorage generation3.

FIG. 40C illustrates initial steps of the example of the retrieving of the stored data to reproduce thedata352, where theinbound DST processing82 receives a read request regarding the data, where the read request includes thedata name354. Having received thedata name354, theinbound DST processing82 estimates likely retrieval data storage information. Alternatively, theslice name module350 estimates the likely retrieval data storage information. As a specific example, theslice name module350 determines a logical DSN address to physical storage device mapping (e.g., identifies DSN address ranges corresponding to each current storage generation). As another specific example, theslice name module350 determines historical use patterns of the DSN memory (e.g., which storage generations hold the most retrieval data). As yet another specific example, theslice name module350 determines historical storage patterns of a requesting entity that is requesting the read request (e.g., identify likely storage generations associated with storage of retrieval data associated with the requesting entity).

Having estimated the likely retrieval data storage information, theslice name module350 generates likely DSN retrieval data addresses358 based on thedata name354 and the likely retrieval data storage information. As a specific example, theslice name module350 generates the likely DSN retrieval data addresses358 to includegeneration3 when the likely retrieval data storage information includes identification ofstorage generation3.

With the likely DSN retrieval data addresses358 being generated, theinbound DST processing82 sends read requests to the likely DSN retrieval data addresses358. As a specific example, theinbound DST processing82 sends, via thenetwork24, retrieval data read requests forgeneration3, that includes a set of read slice requests1-n, to the set of DST execution units associated withstorage generation3. The set of DST execution units1-n issues read slice responses to theinbound DST processing82, where the read slice responses includes encoded retrieval data slices ofgeneration3.

When favorable responses to the read requests have been received, theinbound DST processing82 reconstructs the retrieval data. Having reconstructed the retrieval data, theinbound DST processing82 utilizes the retrieval data to reconstruct the data. The reconstruction of the data is discussed in greater detail with reference toFIG. 40D.

When the favorable responses to the read requests have not been received (e.g., if the read requests were sent tostorage generation4 instead of3), at least one of theinbound DST processing82 and theslice name module350 estimates a second likely retrieval data storage information and generates second likely DSN retrieval data addresses based on the data name and the second likely retrieval data storage information. For example, theslice name module350 generates second likely DSN retrieval data addresses forgeneration3. Having generated the second likely DSN retrieval data addresses, theinbound DST processing82 sends second read requests to the second likely DSN retrieval data addresses. For example, theinbound DST processing82 sends, via thenetwork24, retrieval data read requests forgeneration3 to the set of DST execution units associated withstorage generation3. When favorable responses to the second read requests have been received, theinbound DST processing82 reconstructs the retrieval data and utilizes the retrieval data to reconstruct the data.

Alternatively, or in addition to, at least one of theinbound DST processing82 and theslice name module350 determines to recover the retrieval data from at least two storage generations. The determining includes at least one of interpreting a request, interpreting another system registry entry, and detecting that a system loading level is less than a system loading threshold level. When recovering from the at least two storage generations, at least one of theinbound DST processing82 and theslice name module350 estimates the second likely retrieval data storage information. With the second likely retrieval data storage information, theslice name module350 generates the second likely DSN retrieval data addresses based on thedata name354 and the second likely retrieval data storage information. With the second likely DSN retrieval data addresses, theinbound DST processing82 sends, via thenetwork24, the second read requests to the second likely DSN retrieval data addresses. When favorable responses to either of the read requests or the second read requests have been received, theinbound DST processing82 reconstructs the retrieval data and utilizes the retrieval data to reconstruct the data.

FIG. 40D illustrates final steps of the example of the retrieving of the stored data to reproduce thedata352, where theinbound DST processing82 extracts the DSN data addresses from the reconstructed retrieval data and issues data retrieval requests to theDSTN module22 in accordance with the extracted DSN data addresses. As a specific example, theinbound DST processing82 generates a set of read slice requests that includes the plurality of sets of DSN data addresses based on the extracted DSN data addresses. Having generated the set of read slice requests, theinbound DST processing82 sends the set of read slice requests to the set of DST execution units1-n ofstorage generation3, where the read slice requests includes read slice requests for the plurality of encoded data slices stored instorage generation3. The set of DST execution units1-n ofstorage generation3 sends encoded data slices ofgeneration3 to theinbound DST processing82. Theinbound DST processing82 decodes received encoded data slices to reproduce thedata352.

FIG. 40E is a flowchart illustrating an example of accessing data. The method includes storage where at step360 a processing module (e.g., of a distributed storage and task (DST) client module of a dispersed storage network (DSN)) sends a plurality of sets of encoded data slices to DSN memory for storage in accordance with a plurality of sets of DSN data addresses. The data was dispersed storage error encoded to produce the plurality of sets of encoded data slices. The data has a data name and the plurality of sets of DSN data addresses is generated based on a data object number associated with the data and data storage information. The data name includes file system information. The processing module may utilize a pseudo random number generator to produce the data object number. The processing module may determine, as the data storage information, dispersed storage error encoding parameters.

The method continues atstep362 where the processing module generates retrieval data that is based on the data object number and the data storage information. For example, the processing module generates the retrieval data to include a source name associated with the sets of DSN data addresses. The method continues atstep364 where the processing module dispersed storage error encodes the retrieval data to produce a set of encoded retrieval data slices. The method continues atstep366 where the processing module generates a set of DSN retrieval data addresses based on the data name and on retrieval data storage information. For example, the processing module performs a deterministic function on the data name to produce a retrieval data object number. The processing module may determine, as the retrieval data storage information, dispersed storage error encoding parameters. The method continues atstep368 where the processing module sends the set of encoded retrieval data slices to the DSN memory for storage therein in accordance with the set of DSN retrieval data addresses.

The processing module may facilitate storage of multiple copies of the set of encoded retrieval data slices. The method continues atstep370 where the processing module determines to store multiple copies of the set of encoded retrieval data slices. The method continues atstep372 where the processing module identifies multiple sets of storage units of the DSN memory for storing the multiple copies. The multiple sets of storage units being part of a logical storage vault within the DSN memory, where a first set of storage units of the set of storage units corresponds to a first generation of the DSN memory and a second set of storage units of the set of storage units corresponds to a second generation of the DSN memory.

For each copy of the multiple copies, the method continues atstep374 where the processing module stores the multiple copies in the identified multiple sets of storage units. For example, the processing module generates a unique set of DSN retrieval data addresses based on the data name, on the retrieval data storage information, and on a corresponding one of the multiple sets of storage units. Next, the processing module sends the set of encoded retrieval data slices to the corresponding one of the multiple sets of storage units for storage therein in accordance with the unique set of DSN retrieval data addresses.

When retrieving the data, the method includesstep376 where the processing module receives a read request regarding the data, where the read request includes the data name. The method continues atstep378 where the processing module estimates likely retrieval data storage information (e.g., estimates most probable generations). The estimating the likely retrieval data storage information includes one or more of determining a logical DSN address to physical storage device mapping, determining historical use patterns of the DSN memory, and determining historical storage patterns of a requesting entity that is requesting the read request.

The method continues atstep380 where the processing module generates likely DSN retrieval data addresses based on the data name and the likely retrieval data storage information. The method continues atstep382 where the processing module sends read requests to the likely DSN retrieval data addresses. The processing module may receive responses to the read requests. When favorable write responses to the read requests have been received, the method branches to step390. When the favorable responses to the read requests have not been received, the method continues to step384.

The method continues atstep384 where the processing module estimates second likely retrieval data storage information when the favorable responses to the read requests have not been received. The method continues atstep386 where the processing module generates second likely DSN retrieval data addresses based on the data name and the second likely retrieval data storage information. The method continues atstep388 where the processing module sends second read requests to the second likely DSN retrieval data addresses. When the favorable responses to the read requests or second read requests have been received, the method continues atstep390 where the processing module reconstructs the retrieval data and utilizes the retrieval data to reconstruct the data.

Alternatively, or in addition to, the processing module may attempt to recover the retrieval data from multiple potential storage locations. As a specific example, the processing module estimates the second likely retrieval data storage information and generates the second likely DSN retrieval data addresses based on the data name and the second likely retrieval data storage information. The processing module sends the second read requests to the second likely DSN retrieval data addresses. When the favorable responses to either of the read requests or the second read requests have been received, the processing module reconstructs the retrieval data and utilizes the retrieval data to reconstruct the data.

FIG. 41 is a flowchart illustrating an example of updating a dispersed storage network (DSN) address. The method includesstep400 where a processing module (e.g., of a distributed storage and task (DST) processing unit) determines to adjust a number of generations associated with a data object stored in a dispersed storage network (DSN). The determining may include at least one of determining to add a generation when an amount of data associated with the data is growing and determining to delete a generation when the amount of data associated with the data a shrinking.

The method continues atstep402 where the processing module identifies a number of generations associated with the data. The identifying includes looking up a current number of generations associated with the data for a write request and estimating a number of generations that existed when the data was written when the access is the read request. The method continues atstep404 where the processing module generates a generation number based on the number of generations. The generating includes performing a deterministic function on the data identifier and the number of generations to produce the generation number. For example, the processing module obtains at least a portion (e.g., a vault identifier (ID) field entry, an object number field entry) of a dispersed storage network (DSN) address associated with the data, performs a deterministic function on the portion of the DSN address to produce a source name reference, and taking the source name reference modulo number of generations to produce the generation number.

The method continues atstep406 where the processing module generates a DSN address using the generation number and based on the data. For example, the processing module utilizes the generation number in a generation field of the DSN address, obtains a data ID, performs a registry lookup to identify the vault ID for a vault ID field of the DSN address based on an accessing entity ID, and obtains an object number for an object number field of the DSN address associated with the data ID (e.g., look up in a directory or a dispersed hierarchical index; generate as a random number when writing the data). The method continues atstep408 where the processing module identifies a set of storage units based on the DSN address. The identifying includes at least one of performing a DSN address-to-physical address table lookup using the DSN address, initiating a query, and performing a generation-to-storage set table lookup using the generation number.

The method continues atstep410 where the processing module accesses the set of storage units using the DSN address to retrieve a plurality of sets of encoded data slices associated with the data. For example, the processing module generates and sends a plurality of sets of read slice requests to the set of storage units and receive a plurality of at least a decode threshold number of read slice responses for each of the sets of read slice requests. The method continues atstep412 where the processing module identifies an updated number of generations associated with the data. The identifying includes adding or subtracting a generation based on one or more of a volume of stored data trend, a request, receiving an error message, and detecting a new set of storage units. For example, the processing module determines to add a new generation when detecting the new set of storage units. As another example, the processing module determines to delete a generation when detecting that a current volume of stored data is less than a low store data threshold level.

The method continues atstep414 where the processing module generates an updated generation number based on the updated number of generations. For example, the processing module performs a deterministic function on a data identifier and the updated number of generations to produce the updated generation number. The method continues atstep416 where the processing module generates an updated DSN address using the updated generation number and based on the data. The generating includes at least one of obtaining a data identifier, performing a lookup based on a vault identifier, obtaining an object number, and performing a lookup. The lookup may include one or more of accessing a registry, accessing a directory, and accessing a dispersed hierarchical index. The method continues atstep418 where the processing module identifies another set of storage units based on the updated DSN address. The identifying includes at least one of performing a lookup, initiating a query, and identifying the other set of storage units based on the updated generation number of the updated DSN address.

The method continues atstep420 where the processing module accesses the other set of storage units using the updated DSN address to store the plurality of sets of encoded data slices associated with the data. The accessing includes issuing one or more sets of write slice requests to the other set of storage units where the requests includes slice names based on the updated DSN address. When the plurality of sets of encoded data slices have been successfully stored, the method continues atstep422 where the processing module deletes the plurality of sets of encoded data slices from the set of storage units using the DSN address. The deleting includes issuing one or more sets of delete slice requests to the set of storage units that includes slice names based on the DSN address.

FIG. 42 is a flowchart illustrating an example of accessing an encoded data slice, which includes similar steps toFIG. 41. The method includesstep424 where a processing module (e.g., of a distributed storage and task (DST) execution unit) receives a read slice request that includes a slice name, where the slice name includes a generation number. The method continues atstep426 where the processing module determines whether the generation number is associated with a locally stored encoded data slice. The determining may be based on accessing a local slice list. The method continues withstep402 ofFIG. 41 where the processing module identifies a number of generations associated with the data.

The method continues atstep428 where the processing module generates an alternate generation number based on the generation number and the number of generations. The processing module may increment or decrement the generation number based on a comparison of another generation number that is associated with locally stored encoded data slices and perform a deterministic function on the data identifier and the number of generations. The method continues atstep430 where the processing module generates an alternate slice name using the alternate generation number and the slice name. The generating includes replacing the generation number with the alternate generation number in the slice name to produce the alternate slice name.

The method continues atstep432 where the processing module identifies another storage unit based on the alternate slice name. The identifying includes accessing a list of storage units associated with a set of generation number is associated with the slice name. The method continues atstep434 where the processing module retrieves an encoded data slice from the other storage units using the alternate slice name. The retrieving includes issuing a read slice requests to the other storage unit, where the request includes the alternate slice name. The processing module receives the encoded data slice from the other storage unit. The method continues atstep436 where the processing module outputs the encoded data slice to a requesting entity. Alternatively, or in addition to, the processing module stores the encoded data slice in a local memory and updates slice location information.

FIGS. 43A, 43C-F are schematic block diagrams of an embodiment of a dispersed storage network (DSN) illustrating an example of time-based storage of data. The DSN includes the distributed storage and task (DST)client module34 ofFIG. 1, thenetwork24 ofFIG. 1, and the distributed storage and a DST execution (EX)unit set438. The DST execution unit set438 includes a set of DST execution units1-5. Each DST execution unit may be implemented utilizing theDST execution unit36 ofFIG. 1. Hereafter, the DST execution unit set438 may be referred to interchangeably as one or more of DSN memory, a set of storage units, and a storage unit set; and the DST execution unit may be referred to interchangeably as a storage unit.

TheDST client module34 includes theoutbound DST processing80 ofFIG. 3. TheDST client module34 may further include a dispersed storage (DS)module441. TheDS module441 may be implemented utilizing a plurality of processing modules. For instance, the plurality of processing modules may include theprocessing module84 ofFIG. 3. As a specific example, the plurality of processing module includes a first module, a second module, a third module, and a fourth module. The first through fourth modules may be utilized to implement theoutbound DST processing80. The DSN functions to time-based store alarge data object442 in the DST execution unit set438. Thelarge data object442 may include at least one of a video file, a records file, a collection of images file a documentation file, or any other data object that has a data object size greater than a size threshold level, where the size threshold level is associated with a storage process that has a time to completion of storage that compares unfavorably to a potential change in availability of the DST execution unit set438. For example, the availability of the DST execution unit set438 may change during a time frame that the large data object is being stored to the DST execution unit set438.

FIG. 43A illustrates initial steps of an example of the storing of thelarge data object442, where theoutbound DST processing80 receives thelarge data object442. Having received thelarge data object442, theoutbound DST processing80 encodes thelarge data object442 in accordance with a dispersed storage error coding function to produce a plurality of sets of encoded data slices. As a specific example, theoutbound DST processing80 generates encoded data slice sets1-M as the plurality of sets of encoded data slices and temporarily stores the encoded data slice sets1-M in asend queue440.

Having cached the encoded data slice sets1-M, theoutbound DST processing80 obtains estimated future availability information for storage units of the DSN. As a specific example, theoutbound DST processing80 obtainsavailability information444 from the DST execution unit set438. Theavailability information444 includes one or more of an expected pattern of availability, expected start time of and availability level transition, expected duration of a next availability period, a maintenance schedule, a historical availability record, and an indication of a pending software update. As a specific example, the set of DST execution units1-5 send, via thenetwork24, availability information1-5 as theavailability information444 to theoutbound DST processing80. Having received theavailability information444, theoutbound DST processing80 interprets theavailability information444 to produce the estimated future availability information for the storage units. The generation and utilization of the estimated future availability information is discussed in greater detail with reference toFIG. 43B.

FIG. 43B is a timing diagram illustrating an example of generating a time-availability pattern. The timing diagram includes a mapping of the estimatedfuture availability information446 versustime448 and to a time-availability pattern450. As a specific example, the mapping of the estimatedfuture availability information446 versustime444 indicates thatDST execution unit1 is expected to be available from a current time of t0 until a time of t2, unavailable from t2 to t8 due to a scheduled software update, and available again from t8 to t10. The example mapping also indicates thatDST execution unit2 is expected to be available from t0 to t5, unavailable from t5 to t8 due to scheduled maintenance, and available from t8 to t10. The example mapping also indicates thatDST execution unit3 is expected to be available from t0 to t6 and unavailable from t6 to t10 due to a scheduled power shutdown. The example mapping also indicates thatDST execution units4 and5 are expected to be available from t0 to t10.

Having obtained the estimatedfuture availability information446, theoutbound DST processing80 ofFIG. 43A organizes the plurality of sets of encoded data slices into a plurality of group-sets of encoded data slices, where a group-set of encoded data slices includes multiple sets of encoded data slices. As a specific example, theoutbound DST processing80 organizes encoded slice sets1 through M1 (e.g., of encoded slice sets1-M) into a first group-set of encoded data slices to be associated with a first write transaction, encoded slice sets M1+1 through M2 into a second group-set of encoded data slices to be associated with a second write transaction, encoded slice sets M2+1 through M3 into a third group-set of encoded data slices to be associated with a third write transaction, and encoded slice sets M3+1 through M into a fourth group-set of encoded data slices to be associated with a fourth write transaction.

For each of the plurality of group-set of encoded data slices, theoutbound DST processing80 estimates an approximate storage completion time to produce a plurality of approximate storage completion times. The estimating of the approximate storage completion time may be based on one or more of a network performance level of thenetwork24, a loading level for the DST execution unit set438, a previous write transaction, a number of encoded data slices of the group-set of encoded data slices, and a size of each of the encoded data slices. As a specific example, theoutbound DST processing80 estimates that the first group-set of encoded data slices has an approximate storage completion time of a time duration associated with a time from t0 to t2.

Having estimated the approximate storage completion times, theoutbound DST processing80 obtains a write threshold number. The write threshold number includes a minimum number of available storage units of the set of storage units to facilitate favorable write transactions of each of the group-sets of encoded data slices. The write threshold number is greater than or equal to a decode threshold number and is less than or equal to an information dispersal algorithm (IDA) width, where the decode threshold number and IDA width are associated with the dispersed storage error coding function. The IDA width includes a number of encoded data slices of each set of encoded data slices and the decode threshold number includes a minimum number of encoded data slices required to recover data associated with a set of encoded data slices.

Having obtained the write threshold number, theoutbound DST processing80 establishes the time-availability pattern450 for writing the plurality of group-sets of encoded data slices to the storage units based on the estimated future availability information, the plurality of approximate storage completion times, and the write threshold number. The time-availability pattern450 includes a plurality of time intervals and an availability indication for each of the storage units in each time interval of the plurality of time intervals. The storing of a group-set of the plurality of group-sets of encoded data slices spans at least one time interval of the plurality of time intervals.

As a specific example of the time-availability pattern450, theoutbound DST processing80 establishes the time-availability pattern450 to include writing the first group-set of encoded data slices during time interval t0-t2 when all five storage units are expected to be available, writing the second group-set of encoded data slices during time interval t2-t5 when four of the five storage units are available and the write threshold number is three, writing the third group-set of encoded data slices during time interval t5-t6 when three of the five storage units are available and the write threshold number is three, performing no writing during time interval t6-t8 when less than the write threshold number of storage units are expected to be available, and writing the fourth-set of encoded data slices during time interval t8-t10 when four of the five storage units are expected to be available and the write threshold number is three.

The time-availability pattern450 may further include an indication to send or withhold particular encoded data slices of a given set of encoded data slices based on the estimatedfuture availability information446. As a specific example, theoutbound DST processing80 determines to withhold sending encoded data slices toDST execution unit1 during the timeframe t2-t5 associated with the second write transaction whenDST execution unit1 is expected to be unavailable. For instance, theoutbound DST processing80 holds encoded data slices associated withDST execution unit1 in thesend queue440 during time interval t2-t8 and sends the held encoded data slices (e.g., unwritten encoded data slices from the second and third write transactions) to theDST execution unit1 over the time interval t8-t10.

FIG. 43C illustrates further steps of an example of the storing of thelarge data object442, where theoutbound DST processing80 sends the plurality of group-sets of encoded data slices to at least some of the storage units for storage in accordance with the time-availability pattern450. The sending includes, for each of the plurality of group-set of encoded data slices, theoutbound DST processing80 assigning a transaction number (e.g., transaction numbers1-4 for the four group-sets of encoded data slices) and generating a write request for each available storage unit per the time-availability pattern450 to produce a set of write requests, where each write request of the set of write requests includes the transaction number. As a specific example, theoutbound DST processing80 initiates awrite transaction1 at time t0. For instance, theoutbound DST processing80 sends, via thenetwork24, a set of write slice requests1-1 through1-5 to DST execution units1-5, where the set of write slice request includes the first group-set of encoded data slices and thetransaction number1.

When, sending a given group-set of the plurality of group-sets of encoded data slices, one of the storage units was listed as unavailable, theoutbound DST processing80 queues sending an encoded data slice of each set of the given group-set of encoded data slices and when the one of the storage units is available and when another given group-set of the plurality of group-sets of encoded data slices is being sent to the storage units, theoutbound DST processing80 sends the encoded data slice of each set of the given group-set of encoded data slices to the one of the storage units.

FIG. 43D illustrates further steps of an example of the storing of thelarge data object442, where theoutbound DST processing80 compares, as time passes, actual availability information of the storage units with corresponding time portions of the estimatedfuture availability information446. As a specific example, theoutbound DST processing80 re-obtains theavailability information444 from the DST execution unit set438 prior to time t2. When the actual availability information does not substantially match the estimatedfuture availability information446 for the corresponding time portions, theoutbound DST processing80 adjusts the time-availability pattern450 based on a difference between the actual availability information and estimated future availability information for the corresponding time portions. For instance, theoutbound DST processing80 suspends sending of a next group-set of encoded data slices when the actual availability information for a next time frame indicates that less than the write threshold number of storage units are estimated to be available.

Alternatively, or in addition to, when, during the sending a given group-set of the plurality of group-sets of encoded data slices, less than the write threshold number of storage units are available, theoutbound DST processing80 ceases the sending of the given group-set of the plurality of group-sets of encoded data slices and queues the given group-set of the plurality of group-sets of encoded data slices for sending to the at least some of the storage units when at least the write threshold number of storage units are available.

FIG. 43E illustrates further steps of an example of the storing of thelarge data object442, where theoutbound DST processing80 initiates awrite transaction2 at time t2. For instance, theoutbound DST processing80 sends, via thenetwork24, a set of write slice requests2-1 through2-5 to DST execution units1-5, where the set of write slice request includes the second group-set of encoded data slices and thetransaction number2.

FIG. 43F illustrates further steps of an example of the storing of thelarge data object442, where theoutbound DST processing80 compares further actual availability information of the storage units with corresponding time portions of the estimatedfuture availability information446. As a specific example, theoutbound DST processing80 re-obtains theavailability information444 from the DST execution unit set438 prior to time t5 and interprets there-obtained availability information444 to produce the further actual availability information. When the further actual availability information does not substantially match the estimatedfuture availability information446 for the corresponding time portions, theoutbound DST processing80 adjusts the time-availability pattern450 based on a difference between the further actual availability information and estimated future availability information for the corresponding time portions.

FIG. 43G is a flowchart illustrating an example of time-based storage of data. In particular, a method is presented for use in conjunction with one or more functions and features described in conjunction withFIGS. 1-39 and alsoFIGS. 43A-F. The method includesstep460 where a processing module (e.g., of a distributed storage and task (DST) client module of a dispersed storage network (DSN)) obtains estimated future availability information for storage units of the DSN. For example, the processing module receives the estimated future availability information from the storage units.

The method continues atstep462 where the processing module organizes a plurality of sets of encoded data slices into a plurality of group-sets of encoded data slices. A group-set of encoded data slices includes multiple sets of encoded data slices. The data is encoded in accordance with a dispersed storage error coding function to produce the plurality of sets of encoded data slices. Dispersal parameters are associated with the dispersed storage error coding function. The dispersal parameters includes one or more of an information dispersal algorithm width (e.g., a number of encoded data slices of each set of encoded data slices), a write threshold number (e.g., a subset number of the IDA width required to successfully write a representation of the set of encoded data slices to the storage units), and a decode threshold number (e.g., a minimum number of encoded data slices of the set of encoded data slices required to recover data represented by the set of encoded data slices).

For each of the plurality of group-sets of encoded data slices, the method continues atstep464 where the processing module estimates an approximate storage completion time to produce a plurality of approximate storage completion times. The method continues atstep466 where the processing module obtains the write threshold number (e.g., retrieves from system registry information, receives, determines based on storage requirements and a system performance level).

The method continues atstep468 where the processing module establishes a time-availability pattern for writing the plurality of group-sets of encoded data slices to the storage units based on the estimated future availability information, the plurality of approximate storage completion times, and the write threshold number. The establishing may include comparing, as time passes, actual availability information of the storage units with corresponding time portions of the estimated future availability information and when the actual availability information does not substantially match the estimated future availability information for the corresponding time portions, adjusting the time-availability pattern based on a difference between the actual availability information and estimated future availability information for the corresponding time portions.

The method continues atstep470 where the processing module sends the plurality of group-sets of encoded data slices to at least some of the storage units for storage in accordance with the time-availability pattern. The sending includes, for each of the plurality of group-sets of encoded data slices, assigning a transaction number and generating a write request for each available storage unit per the time-availability pattern to produce a set of write requests, where each write request of the set of write requests includes the transaction number. Alternatively, or in addition to, when, for the sending of a given group-set of the plurality of group-sets of encoded data slices, one of the storage units was listed as unavailable, the processing module queues sending an encoded data slice of each set of the given group-set of encoded data slices. When the one of the storage units is available and when another given group-set of the plurality of group-sets of encoded data slices is being sent to the storage units, the processing module sends the encoded data slice of each set of the given group-set of encoded data slices to the one of the storage units.

Alternatively, or in addition to, when, during the sending a given group-set of the plurality of group-sets of encoded data slices, less than the write threshold number of storage units are available, the processing module ceases the sending of the given group-set of the plurality of group-sets of encoded data slices and queues the given group-set of the plurality of group-sets of encoded data slices for sending to the at least some of the storage units when at least the write threshold number of storage units are available.

FIG. 44A is a schematic block diagram of another embodiment of a distributed storage and task (DST)execution unit36 ofFIG. 11. TheDST execution unit36 includes aninterface169, thememory88, thecontroller86, a plurality of distributed task (DT)execution modules90, and a plurality ofDST client modules34. In an example of operation, thecontroller86 obtains status of the plurality ofDT execution modules90 and the plurality ofDST client modules34. The obtaining includes one or more of issuing atask control message480 to the plurality ofDT execution modules90, issuing aDST control message482 to the plurality ofDST client modules34, receiving atask control message480 from one or more of theDT execution modules90 that includes the status, and receiving aDST control message482 from one or more of theDST client modules34 that includes the status. The status includes one or more of processing utilization level information, memory utilization level information, garbage collection logs, error information, and pending activity information.

In an example of operation, thecontroller86 receives a request via theinterface169, where the request includes at least one of a slice processing request and apartial task98. Thecontroller86 identifies a resource type based on the request (e.g., a DT execution module type for thepartial task98 and a DST client module type for the slice processing request). Thecontroller86 determines whether the resource type is available based on the status. When the resource type is available, thecontroller86 selects a particular resource for assignment of the request. For example, thecontroller86 identifies a thirdDST client module34 that is most available for the request when the request is the slice processing request. As another example, thecontroller86 selects a fourthDT execution module90 when the fourthDT execution module90 is associated with processing resources capable of executing thepartial task98 when the request is thepartial task98. Thecontroller86 assigns the request to the selected resource. The assigning includes at least one of outputting an assignment task control message to an assignedDT execution module90 and outputting an assignment DST control message to the assigned DST client module. When the resource type is not available, thecontroller86 may issue an error response via theinterface169 to a requesting entity and/or to a managing unit.

The assignedDT execution module90 executes the assignedpartial task98 to producepartial results102. Alternatively, or in addition to, the assignedDT execution module90 facilitates thememory88 to retrieveslices96 and to output results104. The assignedDST client module34 executes the slice processing request to facilitate producing at least one ofsub-slice groupings170 and sub-partialpartial tasks172. Alternatively, or in addition to, theDST client module34 may facilitate thememory88 to provideslices100 and/or two receivesslices96 for further slice processing.

FIG. 44B is a flowchart illustrating an example of assigning resources. The method includesstep484 where a processing module (e.g., of a controller module) obtains resource status information for a plurality of task execution modules and a plurality of dispersed storage modules. The obtaining includes at least one of receiving, issuing a query, performing a lookup, accessing a historical record, and interpreting an activity log. The method continues atstep486 where the processing module receives a request. The method continues atstep488 where the processing module identifies a resource type based on the request. For example, the processing module identifies the resource type based on a type of the request. For instance, the processing module identifies a distributed task execution module receiving a partial task requests. In another instance, the processing module identifies a distributed storage and task client module type when receiving a slice processing request. The processing module may identify another resource type for another request type.

The method continues atstep490 where the processing module determines whether the resource type is available. For example, for each resource, the processing module interprets pending request to produce a predicted loading level and compares the predicted loading level to an upper loading level threshold. The processing module indicates availability when the comparison is favorable (e.g., more capacities available than required). The method branches to step494 when the resource type is available. The method continues to step492 when the resource type is not available. The method continues atstep492 where the processing module issues an error response when the resource type is not available. The issuing of the error response includes generating an error message and sending the error message to at least one of a requesting entity and a managing unit.

The method continues atstep494 where the processing module selects at least one resource of the plurality of task execution modules and the plurality of dispersed storage modules when the resource type is available. For example, the processing module identifies a resource associated with a most favorable comparison of predicted loading to available loading (e.g., most available capacity). The method continues atstep496 where the processing module assigns the request to the selected at least one resource. For example, the processing module sends the request to the selected resource.

FIG. 45A is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system that includes the distributed storage and task network (DSTN)module22 ofFIG. 1, a set of distributed storage and task (DST) processing units1-N, where each DST processing unit includes theDST processing unit16 ofFIG. 1, and a load-balancingmodule498. TheDSTN module22 includes the DST execution unit set438 ofFIG. 43A. The DST execution unit set438 includes a set ofDST execution units36 ofFIG. 1.

The system functions to storedata500 as a plurality of sets of encoded data slices504 in the DST execution unit set438. The load-balancingmodule498 selects one of the DST processing units, based on resource status information502 from the DST processing units, to encode thedata500 using a dispersed storage error coding function to produce the plurality of sets of encoded data slices504 for storage in the DST execution unit set438. The resource status information502 includes one or more of an indicator of a time frame of availability, an indicator of a time frame of unavailability, a time frame for a scheduled software update, a time frame for a scheduled new hardware addition, an error message, a maintenance schedule, a communications error rate, and a storage error rate.

In an example of operation, a DST processing unit determines to at least temporarily suspend operations. The determining may be based on one or more of adding new software, activating new hardware, recovering from a storage error, recovering from a communications error, receiving a suspend request, and interpreting the maintenance schedule. The DST processing unit continues to perform a slice access activity with regards to pending data access requests associated with the DST processing unit. The load-balancingmodule498 receives a new data access request. The load-balancingmodule498 determines availability of each of the DST processing units based on one or more of receiving resource status information502, initiating a query, receiving an error message, and detecting an unfavorable performance (e.g., detecting slow response latency). The load-balancingmodule498 selects the DST processing unit when the availability (e.g., previously known availability) of the DST processing unit compares favorably to availability of other DST processing units. The load-balancingmodule498 forwards the data access requests to the DST processing unit.

While suspending operations, the DST processing units indicates the unfavorable performance to the load-balancing module. The indicating unfavorable performance includes at least one of ignoring the request, sending a late unfavorable response, issuing unfavorable resource status information, and ignoring resource status requests from the load-balancing module. The load-balancingmodule498 interprets the indication to determine that the data access request is to be reassigned. The load-balancingmodule498 un-selects the DST processing unit from the data access assignment. For example, the load-balancing module sends a cancellation message to the DST processing unit and selects another DST processing unit and sends the data access request to the other DST processing unit.

FIG. 45B is a diagram illustrating an example of load-balancing. The method includes step506 where a distributed storage and task (DST) processing unit determines to temporarily suspend operations. The method continues atstep508 where the DST processing unit continues to execute pending operations. For example, the DST processing unit continues to process previously accepted data access requests. The method continues atstep510 where a load-balancing module receives a data access request. The method continues atstep512 where the load-balancing module assesses availability of a set of DST processing units that includes the DST processing unit. The assessing includes producing availability information based on one or more of interpreting performance indicators, receiving resource status information, initiating a query, receiving an error message, and detecting favorable performance.

The method continues atstep514 where the load-balancing module selects the DST processing unit for execution of the data access request. For example, the load-balancing module selects the DST processing unit when availability of the DST processing unit compares more favorably to availability of other DST processing units. The method continues atstep516 where the load-balancing module forwards the data access request to the DST processing unit.

The method continues atstep518 where the DST processing unit indicates unfavorable performance. For example, the DST processing unit ignores the data access requests. As another example, the DST processing unit waits a delay time period before sending a data access response causing the load-balancing module to interpret the data access response as a late data access response associated with unfavorable performance. As yet another example, the DST processing unit delays responses associated with previous accepted data access requests. The method continues atstep520 where the load-balancing module detects the indicated unfavorable performance. For example, the load-balancing module detects the indicated unfavorable performance when the data access response was not received within a desired response timeframe.

The method continues atstep522 where the load-balancing module un-selects the DST processing unit for execution of the data access request. The un-selecting includes one or more of sending a cancellation message to the DST processing unit, selecting another DST processing unit for the data access request, and assigning the other DST processing unit the data access request.

The method continues atstep524 where the DST processing unit determines to resume operations. The determining may be based on one or more of detecting that new software is operational, detecting that new hardware is operational, detecting that an error condition has cleared, and detecting that a level of pending data access requests has fallen below a low data access request threshold level. The method continues atstep526 where the DST processing unit indicates favorable performance. For example, the DST processing unit generates data access responses in accordance with desired data access response timing. As another example, the DST processing unit responds to all data access requests. As yet another example, the DST processing unit sends favorable resource status information to the load-balancing module.

FIG. 46A is a schematic block diagram of another embodiment of a distributed storage and task (DST)execution unit36 that includes the distributed storage and task (DST)client module34 and one ormore memory devices88 ofFIG. 3. Thememory88 includes a plurality of portions of memory associated with different utilizations. The portions may be physical memory or virtual memory space. The plurality of portions includes one or more portions utilized forslices memory606, utilized for rebuiltslices memory608, reserved for rebuilt slices memory610, andun-utilized memory612. Theun-utilized memory612 is associated with available storage capacity, where the available storage capacity may be calculated as a memory size minus memory used for each of the utilized forslices memory606, memory used for the utilized for rebuiltslices memory608, and memory used for the reserved for rebuilt slices memory610.

TheDST execution unit36 functions to store encoded data slices600 in the utilized forslices memory606 and store rebuilt encoded data slices602 in the utilized for rebuiltslices memory608. TheDST client module34 may obtain the rebuilt encoded data slices by at least one of: receiving the rebuilt encoded data slices and generating the rebuilt encoded data slices by retrieving representations of encoded data slices from a decode threshold number of otherDST execution units36. When encoded data slices are to be stored, theDST client module34 determines whether sufficient available storage capacity of the un-utilized memory is available for utilization for slices memory. For instance, the DST client module compares a size of an encoded data slice for storage to the size of the un-utilized memory. The DST client module indicates that storage space is available when the size of the encoded data slice is less than the size of the un-utilized memory. TheDST client module34 may determine the size of the reserved for rebuilt slices memory based on identifying encoded data slices to be rebuilt. The identifying includes at least one of detecting a slice error and receiving an indication of the slice error.

In an example of operation, theDST client module34 identifies a plurality of encoded data slices requiring rebuilding. TheDST client module34 determines an amount of reserve memory610 required for storage of rebuilt slices for the identified plurality of encoded data slices requiring rebuilding. The determining may include exchangingmemory utilization information604 with at least one other DST execution unit, where the exchanging includes receiving an amount of memory required for an encoded data slice associated with, for example, a slice error. TheDST client module34 updates the memory utilization information to include the amount of reserve memory required. The memory utilization information includes one or more of size of the utilized for slices memory, size of the utilized for rebuilt slices memory, size of the reserved for rebuilt slices memory, and size of the un-utilized memory. TheDST client module34 outputs thememory utilization information604 to one or more of a DST processing unit, a managing unit, and a user device.

TheDST client module34 obtains rebuilt encoded data slices (e.g., receives, generates) and stores the rebuilt encoded data slices in the utilized for rebuilt encoded data slices memory. Accordingly, the DST client module updates the reserved for rebuilt slices memory by a similar memory size amount as storage of the rebuild encoded data slices (e.g., lowers size of reserved for rebuilt slices memory and raises size for utilized for rebuilt slices memory). The DST client module updates the memory utilization information and may output the updated memory utilization information.

FIG. 46B-C are diagrams illustrating examples of memory utilization for a series of times frames, where each timeframe indicates an amount of memory utilized for slices, rebuilt slices, reserved for rebuilt slices, unutilized, and a total amount of memory capacity. The total amount of memory capacity remains constant over the time intervals. In particular,FIG. 46 B illustrates examples of thememory utilization614 for a first set of time intervals T1-5. At T1, stored slices use 300 TB of memory space of a total capacity of 500 TB of memory space leaving 200 TB of unutilized memory space. At T2, 50 TB of slices for rebuilding are detected such that reserved for rebuilding is incremented by 50 TB and unutilized memory space is lowered by 50 TB from 200 TB to 150 TB. At T3, a first 20 TB of rebuilt slices are obtained and stored such that the reserved memory space for rebuilt slices is lowered by 20 TB from 50 TB to 30 TB. At T4, a remaining 30 TB of rebuilt slices are obtained and stored such that the reserve memory space rebuilt slices is lowered by another 30 TB from 30 TB two 0 TB and the rebuilt slices is raised to buy 30 TB from 20 TB to 50 TB. At T5, the rebuilt slices are moved to the memory space for slices thus raising the rebuilt slices by 50 TB from 300 TB to 350 TB. Utilized memory includes thecombination615 of utilized forslices memory606, memory used for the utilized for rebuiltslices memory608, and memory used for the reserved for rebuilt slices memory610.

FIG. 46C continues the examples ofmemory utilization616 for second set of time intervals T6-T10. The example begins at time interval T6 which is equivalent to memory utilization of T5. At T7, 100 TB of new slices are stored thus raising the memory utilization of slices from 350 TB to 450 TB and lowering the unutilized memory space from 150 TB to 50 TB. At T8, 50 TB of slices for rebuilding is detected such that memory space of reserved for rebuilding is incremented by 50 TB from zero to 50 TB and memory space of unutilized is lowered by 50 TB from 50 TB two 0 TB. Requests for storage of new slices are rejected since the memory space of the unutilized memory is zero. At T9, 50 TB of rebuilt slices are received and stored in the memory space of the rebuilt slices thus raising the rebuilt slices from 0 TB to 50 TB and lowering the memory space for rebuilt slices from 50 TB to 0 TB. At T10, the slices of the memory space rebuilt slices is considered part of the memory space of slices thus raising the memory space of the slices from 450 TB to 500 TB and lowering the memory space of the rebuilt slices from 50 TB to 0 TB. As such, the memory storage space is full and subsequent request for storage of slices or rebuilt slices shall be rejected.

FIG. 46D is a flowchart illustrating an example of updating memory utilization information. The method begins atstep618 where a processing module (e.g., of a distributed storage and task (DST) client module) identifies a plurality of encoded data slices requiring rebuilding. As further delineated inFIG. 46E (flowchart illustrating example ways to identify slices needing a rebuild), the identifying includes at least one of: receiving an error message632 (e.g., no slices detected for rebuild, no access to rebuild information, not enough space to rebuild, etc.); receiving a rebuilding request634 (e.g., to rebuild specific data slices or range of data slices); detecting missing or corrupted encoded data slices by comparing a list of locally stored encoded data slices (or range of slices) to a list of remotely stored encoded data slices (or range of slices) associated with the locally stored encoded data slices to identify missing slices or detecting unfavorable slice integrity (e.g., corrupted slices); monitoring downloads638 to the DS memory meeting minimum read/write (R/W) width thresholds but less than a full pillar width (successful download, but not all slices above threshold successfully downloaded); determining640 when DSN read/write (R/W) requests occur for the plurality of encoded data slices and comparing to known times of inaccessibility for the DS memory storing the plurality of encoded data slices (e.g., DS memory was down for maintenance when original slice R/W request occurred); and querying vaults related to the plurality of encoded data slices641 to determine one or more missing or corrupted encoded data slices (e.g., other vaults sharing the same data slices may have a list or copies which include the missing or corrupted data slices).

The rebuilding of the plurality of encoded data slices is, in one embodiment, queued for at least one of individual, group, or batch processing and the processing will be performed at a significant time delay from the queuing. As the rebuild processing may occur in the future, the embodiments ofFIGS. 46A-G, ensure that memory space is set aside for rebuilds such that interceding requests for memory slice storage will not over utilize memory needed for the rebuild before it has a chance to occur.

The method continues at thestep620 where the processing module determines an amount of memory space to reserve for the plurality of encoded data slices requiring rebuilding. The determining includes identifying slice sizes based on at least one of initiating a slice size query with regards to the remotely stored encoded data slices, receiving a query response, and performing a local lookup based on a slice name.

The method continues atstep622 where the processing module updates memory utilization information to include the amount of memory space to reserve. For example, the processing module increments an amount of memory reserved for rebuilt slices by the amount of memory space to reserve and decrements unutilized memory space by the amount of memory space to reserve. The method continues atstep624 where the processing module sends the memory utilization information to at least one of a storing entity and a managing unit. The sending may further include determining whether a sum of an amount of memory utilized for slices, an amount of memory utilize for rebuilt slices, and an amount of memory reserved for rebuilt slices is greater than a capacity of memory. When the sum is greater, the processing module may further send an indication that the memory is full.

The method continues atstep626 where the processing module obtains rebuilt encoded data slices (e.g., received, generate). The method continues atstep628 where the processing module stores the rebuilt encoded data slices in a local DS memory. The method continues atstep630 where the processing module updates the amount of memory space to reserve for remaining encoded data slices requiring rebuilding. The updating includes determining an amount of memory space utilized to store the obtained rebuilt encoded data slices, incrementing the amount of memory space utilized for rebuilt slices by the amount of memory space utilized to store the obtained rebuilt encoded data slices, and decrementing the amount of memory space reserved for rebuilt slices by the amount of memory space utilized to store the obtained rebuilt encoded data slices. The updating may further include updating the memory space utilized for slices to include the amount of memory space utilized to store the obtained rebuilt encoded data slices and decrementing the amount of memory space utilized to store the rebuild encoded data slices. The method loops back to the step where the processing module updates the memory utilization information.

FIG. 46F is a flowchart illustrating another example of updating memory utilization information. The method begins atstep642 where a processing module (e.g., DST integrity processing unit20) attempts to retrieve a plurality of encoded data slices from a DS memory to perform an integrity check. Slices are retrieved based on any of: list(s) of slice addresses, list(s) of names, range(s) of slice addresses and range(s) of slice names. Instep644, it is determined if the encoded data slices were retrieved during the attempted retrieval. Instep646, for encoded data slices that were not received and/or not listed, they are flagged as missing slices. For retrieved encoded data slices, they are checked for errors due to data corruption, outdated version, etc. Instep648, if a slice includes an error, it is flagged as a ‘bad’ slice. Bad and/or missing slices are subsequently rebuilt using other retrieved encoded data slices that are deemed to be good slices to produce rebuilt slices.

The rebuilding of the plurality of encoded data slices is, in one embodiment, queued for at least one of individual, group, or batch processing and the processing will be performed at a significant time delay from the queuing. As the rebuild processing may occur in the future, the embodiments ofFIGS. 47A-G, ensure that memory space is set aside for rebuilds such that interceding requests for memory slice storage will not over utilize memory needed for the rebuild before it has a chance to occur.

The method continues at thestep650 where the processing module determines an amount of memory space to reserve for the plurality of encoded data slices requiring rebuilding. The determining includes identifying slice sizes based on at least one of initiating a slice size query with regards to the remotely stored encoded data slices, receiving a query response, and performing a local lookup based on a slice name.

The method continues atstep652 where the processing module updates memory utilization information to include the amount of memory space to reserve. For example, the processing module increments an amount of memory reserved for rebuilt slices by the amount of memory space to reserve and decrements unutilized memory space by the amount of memory space to reserve. The method continues atstep653 where the processing module sends the memory utilization information to at least one of a storing entity (e.g., storage/vault peers), user units and a managing unit. The sending may further include determining whether a sum of an amount of memory utilized for slices, an amount of memory utilize for rebuilt slices, and an amount of memory reserved for rebuilt slices is greater than a capacity of memory. When the sum is greater, the processing module may further send an indication that the memory is full.

The method continues atstep654 where the processing module obtains rebuilt encoded data slices (e.g., received, generated) and stores, instep656, the rebuilt encoded data slices in a local DS memory. The method continues atstep657 where the processing module updates the amount of memory space to reserve for remaining encoded data slices requiring rebuilding. The updating includes determining an amount of memory space utilized to store the obtained rebuilt encoded data slices, incrementing the amount of memory space utilized for rebuilt slices by the amount of memory space utilized to store the obtained rebuilt encoded data slices, and decrementing the amount of memory space reserved for rebuilt slices by the amount of memory space utilized to store the obtained rebuilt encoded data slices. The updating may further include updating the memory space utilized for slices to include the amount of memory space utilized to store the obtained rebuilt encoded data slices and decrementing the amount of memory space utilized to store the rebuild encoded data slices.

FIG. 46G is a schematic block diagram illustrating an exampleDST client module34 structure for memory utilization.DST client module34 may include a plurality of processing modules (or sub-modules) to perform one or more steps of the embodiments ofFIGS. 46A-F. While this example is shown as seven separate modules, the modules may be combined/separated into any number of modules (local or remote) to complete the various steps and functions of the various embodiments ofFIGS. 46A-F.

As shown, identify module34-1 identifies a plurality of encoded data slices that require rebuilding, wherein rebuilding of the plurality of encoded data slices is queued for at least one of individual, group, or batch processing and the processing will be performed at a significant time delay from the queuing. Determine module34-2 determines an amount of memory required for storage of the rebuild encoded data slices for the plurality of encoded data slices. Update module34-3 updates utilization information of the memory by allocating a portion of available memory to the amount of memory required. Indicate module34-4 indicates the memory utilization (e.g., by sending the updatedutilization information604 of the memory to at least one of a storing entity (e.g., other storage/vault peers) and a managing unit). Obtain module34-5 obtains rebuilt data slices (e.g., from other good copies or related vaults or generates them from other encoded data slices). Store module34-6 stores the rebuilt encoded data slices in the reserve memory; and modify module34-7 modifies the utilization information to reflect the stored rebuilt encoded data slices. Additional modules may be included withinDST client module34 to perform additional tasks (for example, but not limited to, passing encoded data slices to/from slice memory during non-rebuild write/read (W/R) operations). Alternatively, obtain module34-5 and store module34-6 may perform the receive and store slices600 tasks, respectively.

FIG. 47A is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system that includes the disbursing storage and task (DST)processing unit16 and the distributed storage and task network (DSTN)module22 ofFIG. 1. TheDSTN module22 includes at least two DST execution unit sets1-2. Each DST execution unit set includes a set ofDST execution units36 ofFIG. 1. The system functions to store at least two data objects in a common DST execution unit set.

In an example of operation, theDST processing unit16 receives adata object1write request700. TheDST processing unit16 encodesdata object1 using a dispersed storage error coding function to produce first sets (data object1) of encoded data slices700-1,2, . . . n (where n equals the width (number of pillars) of the encoded data slice set). TheDST processing unit16 generates first sets of slice names for the first sets of encoded data slices. TheDST processing unit16 issues one or more sets of data object1 write slice requests to a DST execution unit set1 that includes the first sets of encoded data slices and the corresponding first sets of slice names, where the first sets of slice names fall within a range of slice names associated with the DSTexecution unit set1.

With data object1 stored in the first set ofDST execution units36, theDST processing unit16 receives adata object2co-locate write request702 with regards to storing a second data object in the same set ofDST execution units36 as the first data object (e.g., in the DST execution unit set1). The data object2 co-locate write request includes a data identifier (ID) of the data object to be co-located with (e.g., a data ID of the data object1), a data ID of the second data object (e.g., the data object2 to be co-located), and may include the data (e.g., data object2) to be co-located when it is not already stored within theDSTN module22.

When the data object to be co-located (e.g., the second data object) is included in the data object2 co-locate write request, theDST processing unit16 identifies the set ofDST execution units36 associated with the data ID of data object1 to be co-located with (e.g., the DST execution unit set1). The determining includes accessing one or more of a directory and a dispersed hierarchical index to identify a DSN address associated with the data ID of data object1 to be co-located with and performing a DSN address-to-physical location table lookup to identify the set ofDST execution units36 associated with the data ID of data object1 to be co-located with. Next, the DST processing unit encodes the second data object (data object2) to produce second sets of encoded data slices for storage in the DSTexecution unit set1. TheDST processing unit16 generates second sets of slice names for the second sets of encoded data slices, where the second sets of slice names are based on the first sets of slice names such that the second sets of slice names fall within a range of slice names associated with a range of slice names associated with the set ofDST execution units36 associated with the data ID of data object1 to be co-located with.DST processing unit16 issues data object2 write slice requests to the set ofDST execution units36 associated with the data ID of the data object to be co-located with (e.g., to DST execution unit set1), where the data object2 write slice requests includes the second sets of encoded data slices.

When the data object to be co-located is not included in the data object2 co-locate write request, theDST processing unit16 determines whether the data object to be co-located is already co-located. The determining includes theDST processing unit16 identifying the DST execution unit set associated with storage of the second data object and comparing the identity to the identity of the DST execution unit set associated with storage of the first data object. When data object2 to be co-located is not already co-located (e.g., with data object1), theDST processing unit16 recovers data object2 from the DST execution unit set associated with storage of the second data object (e.g., from DST execution unit set2). The recovering includes issuingdata object2read slice requests704 to the DST execution unit set associated with storage of the second data object and receiving the second sets of encoded data slices (e.g., received from DST execution unit set2). Next, theDST processing unit16 issues the data object2 write slice requests to the set ofDST execution units36 associated with the data ID of the data object1 to be co-located with (e.g., to DST execution unit set1), where the data object2 write slice requests includes the received second sets of encoded data slices and the corresponding second sets of slice names.

FIG. 47B is a diagram illustrating an example of generating an updated slice name for a previously stored encoded data slice of a second data object to be co-located with one or more encoded data slices of a first data object. Theslice name706 has a structure that includes aslice index field708, a vault identifier (ID)field710, ageneration field712, anobject number field714, and asegment number field716. A substantial number of the fields of the slice name structure of a slice name of the previously stored encoded data slice of the second data object are updated to be substantially aligned with corresponding fields of the slice name structure of a slice name of the one or more encoded data slices of the first data object. For example, a vault ID field entry of theprevious data object2slice1 is updated to be substantially the same as a vault ID field entry of data object1slice1. As another example, an object number field entry of theprevious data object2slice1 is updated based on an object number field entry of theprevious data object2slice1 such that the slice name of the updateddata object2slice1 falls within a range of slice names associated with storage of the first data object.

FIG. 47C is a flowchart illustrating an example of co-locating storage of data objects. The method begins atstep718 where a processing module (e.g., a distributed storage and task (DST) processing unit) receives adata object2 co-locate write request to co-locate adata object2 with adata object1 to be co-located with. The write request includes one or more of data identifiers (IDs) for the data object2 to be co-located and the data object1 to be co-located with. The method continues atstep720 where the processing module obtains a plurality of sets of encoded data slices for the data object2 to co-locate. The obtaining includes one of receiving, generating, and retrieving. When receiving, the processing module extracts the plurality of sets of encoded data slices from thewrite request700. When generating, the processing module encodes the data object2 to be co-located using a dispersed storage error coding function to produce the plurality of sets of encoded data slices. When retrieving, the processing module identifies previous sets of slice names utilized to store the plurality of sets of encoded data slices based on a data ID of the data object2 to become co-located, issues one or more sets of read slice requests to a previously utilized set of storage units where the one or more sets of read slice requests includes the previous sets of slice names, and receiving the plurality of sets of encoded data slices704.

The method continues at thestep722 where the processing module generates a plurality of sets of slice names for the plurality of sets of encoded data slices based on addressing information of the data object1 to be co-located with. For example, the processing module generates the plurality of sets of slice names to include a vault ID associated with the data object to be co-located with and an object number field entry that causes the generated plurality of sets of slice names to fall within a slice name range that is associated with a set of storage units where the data object to be co-located with is stored.

The method continues at thestep724 where the processing module stores the plurality of sets of encoded data slices in the set of storage units using the generated plurality of sets of slice names. The storing includes generating one or more sets of write slice requests that includes the plurality of sets of encoded data slices and the generated plurality of sets of slice names and outputting the one or more sets of read slice requests to the set of storage units. When storage of the plurality of sets of encoded data slices in the set of storage units is confirmed, and when the plurality of sets of encoded data slices were retrieved using the previous sets of slice names, the method continues at thestep726 where the processing module deletes the plurality of sets of encoded data slices utilizing the previous sets of slice names. For example, the processing module issues a set of delete slice requests that includes the previous sets of slice names to the previous utilized set of storage units.

FIG. 47D is a flowchart illustrating one example of obtaining the plurality of sets of encoded data slices to be co-located. The obtaining,step720, includes multiple processing paths for receiving, generating, and retrieving the plurality of sets of encoded data slices to be co-located (data object2) based on the location of data object2 at the time of the request. When receiving, the processing module extracts instep727 the ID ofdata object1, ID ofdata object2 and, if included with the request, the plurality of data object2 sets of encoded slices from thewrite request700. When data object2 to be co-located (e.g., the second data object) is included in the data object2 co-locate write request, theDST processing unit16 identifies, beginning withstep730, the set ofDST execution units36 associated withdata ID1 of the data object to be co-located with (e.g., the DST execution unit set1). The determining includes accessing one or more of a directory instep731 and a dispersed hierarchical index instep732 to identify a DSN address associated with data object1 ID to be co-located with and performing a DSN address-to-physical location table lookup instep734 to identify the physical location (PL) address set ofDST execution units36 associated with the data ID of the data object to be co-located with. If data object2 is not already encoded, it is encoded instep729 using a dispersed storage error coding function.

When the data object to be co-located is not included in the data object2 co-locate write request, theDST processing unit16 determines whether the data object to be co-located is already co-located. The determining includes comparingdata object2 PL todata object1 PL. If they are co-located (data object2 PL is stored within a range of addresses for data object1 PL) no further action is required. When data object2 to be co-located is not already co-located, theDST processing unit16 recovers (reads), instep736, the second data object from the DST execution unit set associated with storage of the second data object (e.g., from DST execution unit set2).

FIG. 47E is a schematic block diagram of another embodiment of a dispersed storage network (DSN) system in accordance with the present disclosure.DST processing unit16 may include a plurality of processing modules (or sub-modules) to perform one or more steps of the embodiments ofFIGS. 47A-D. While this example is shown as four separate modules, the modules may be combined or separated into any number of modules (local or remote) to complete the various steps and functions of the various embodiments ofFIGS. 47A-D.

As shown, receive module16-1 operates to receive a data object co-locate write request. Obtain module16-2 operates to obtain a plurality of sets of encoded data slices for a data object to co-locate. Generate module16-3 operates to generate a plurality of sets of slice names for the data object to co-locate based on another plurality of sets of slice names associated with a data object to be co-located with. Store module16-4 operates to store the plurality of sets of encoded data slices in DS memory using the generated plurality of sets of slice names for the data object co-locate.

As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude differences. As may also be used herein, the term(s) “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”. As may even further be used herein, the term “operable to” or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item. As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is thatsignal1 has a greater magnitude thansignal2, a favorable comparison may be achieved when the magnitude ofsignal1 is greater than that ofsignal2 or when the magnitude ofsignal2 is less than that ofsignal1.

As may also be used herein, the terms “processing module”, “processing circuit”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the FIGS. Such a memory device or memory element can be included in an article of manufacture.

The present disclosure has been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claimed disclosure. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality. To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claimed disclosure. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof.

The present disclosure may have also been described, at least in part, in terms of one or more embodiments. An embodiment of the present disclosure is used herein to illustrate the present disclosure, an aspect thereof, a feature thereof, a concept thereof, and/or an example thereof. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process that embodies the present disclosure may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown as field effect transistors (FETs), as one of ordinary skill in the art will appreciate, the transistors may be implemented using any type of transistor structure including, but not limited to, bipolar, metal oxide semiconductor field effect transistors (MOSFET), N-well transistors, P-well transistors, enhancement mode, depletion mode, and zero voltage threshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodiments of the present disclosure. A module includes a processing module, a functional block, hardware, and/or software stored on memory for performing one or more functions as may be described herein. Note that, if the module is implemented via hardware, the hardware may operate independently and/or in conjunction software and/or firmware. As used herein, a module may contain one or more sub-modules, each of which may be one or more modules.

While particular combinations of various functions and features of the present disclosure have been expressly described herein, other combinations of these features and functions are likewise possible. The present disclosure is not limited by the particular examples disclosed herein and expressly incorporates these other combinations.

Claims (10)

What is claimed is:

1. A dispersed storage (DS) module of a dispersed storage network (DSN), the DS module comprises:

a first module, when operable within a computing device, causes the computing device to:

send a plurality of sets of encoded data slices to DSN memory for storage in accordance with a plurality of sets of DSN data addresses, wherein data is dispersed storage error encoded to produce the plurality of sets of encoded data slices, wherein the data has a data name, wherein the plurality of sets of DSN data addresses is generated based on a data object number associated with the data and data storage information, and wherein the data name includes file system information;

a second module, when operable within the computing device, causes the computing device to:

generate retrieval data that is based on the data object number and the data storage information;

a third module, when operable within the computing device, causes the computing device to:

dispersed storage error encode the retrieval data to produce a set of encoded retrieval data slices;

a fourth module, when operable within the computing device, causes the computing device to:

generate a set of DSN retrieval data addresses based on the data name and on retrieval data storage information; and

a fifth module, when operable within the computing device, causes the computing device to:

send the set of encoded retrieval data slices to the DSN memory for storage therein in accordance with the set of DSN retrieval data addresses.

2. The DS module ofclaim 1 further comprises:

the first module, when operable within the computing device, further causes the computing device to:

utilize a pseudo random number generator to produce the data object number; and

determine, the data storage information, from dispersed storage error encoding parameters that include one or more of:

data segmenting information regarding segmenting the data into a plurality of data segments;

a total number of encoded data slices per set of encoded data slices of the plurality of sets of encoded data slices;

a decode threshold number of encoded data slices per the set of encoded data slices;

a read threshold number of encoded data slices per the set of encoded data slices; and

a write threshold number of encoded data slices per the set of encoded data slices.

3. The DS module ofclaim 1, wherein the file system information comprises one or more of:

a user identifier;

a vault identifier; and

a file system path name for the data.

4. The DS module ofclaim 1, wherein the fourth module causes the computing device to generate the set of DSN retrieval data addresses by:

performing a deterministic function on the data name to produce a retrieval data object number; and

determining, the retrieval data storage information, from dispersed storage error encoding parameters that includes one or more of:

a total number of encoded retrieval data slices for the set of encoded retrieval data slices;

a decode threshold number of encoded retrieval data slices for the set of encoded retrieval data slices;

a read threshold number of encoded retrieval data slices for the set of encoded retrieval data slices; and

a write threshold number of encoded retrieval data slices for the set of encoded retrieval data slices.

5. The DS module ofclaim 1 further comprises:

the fifth module, when operable within the computing device, further causes the computing device to:

determine to store multiple copies of the set of encoded retrieval data slices;

identify multiple sets of storage units of the DSN memory for storing the multiple copies; and

for each copy of the multiple copies:

generate a unique set of DSN retrieval data addresses based on the data name, on the retrieval data storage information, and on a corresponding one of the multiple sets of storage units; and

send the set of encoded retrieval data slices to the corresponding one of the multiple sets of storage units for storage in accordance with the unique set of DSN retrieval data addresses.

6. The DS module ofclaim 5 further comprises:

the multiple sets of storage units being part of a logical storage vault within the DSN memory, wherein a first set of storage units of the set of storage units corresponds to a first generation of the DSN memory and a second set of storage units of the set of storage units corresponds to a second generation of the DSN memory.

7. The DS module ofclaim 1 further comprises:

a sixth module, when operable within the computing device, causes the computing device to:

receive a read request regarding the data, wherein the read request regarding the data includes the data name;

estimate likely retrieval data storage information;

generate likely DSN retrieval data addresses based on the data name and the likely retrieval data storage information;

send read requests to the likely DSN retrieval data addresses; and

when favorable responses to the read requests have been received:

reconstruct the retrieval data; and

utilize the retrieval data to reconstruct the data.

8. The DS module ofclaim 7, wherein the sixth module cause the computing device to estimate the likely retrieval data storage information by one or more of:

determining a logical DSN address to physical storage device mapping;

determining historical use patterns of the DSN memory; and

determining historical storage patterns of a requesting entity that is requesting the read request.

9. The DS module ofclaim 7 further comprises:

the sixth module, when operable within the computing device, further causes the computing device to:

when favorable responses to the read requests have not been received:

estimate a second likely retrieval data storage information;

generate second likely DSN retrieval data addresses based on the data name and the second likely retrieval data storage information;

send second read requests to the second likely DSN retrieval data addresses; and

when favorable responses to the second read requests have been received:

reconstruct the retrieval data; and

utilize the retrieval data to reconstruct the data.

10. The DS module ofclaim 7 further comprises:

the sixth module, when operable within the computing device, further causes the computing device to:

estimate a second likely retrieval data storage information;

generate second likely DSN retrieval data addresses based on the data name and the second likely retrieval data storage information;

send second read requests to the second likely DSN retrieval data addresses;

when favorable responses to either of the read requests or the second read requests have been received:

reconstruct the retrieval data; and

utilize the retrieval data to reconstruct the data.

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